A COMPREHENSIVE STUDY ON DATA EXTRACTION IN SINA WEIBOijaia
With the rapid growth of users in social networking services, data is generated in thousands of terabytes
every day. Practical frameworks for data extraction from social networking sites have not been well
investigated yet. In this paper, a methodology for data extraction with respect to Sina Weibo is discussed.
In order to design a proper method for data extraction, the properties of complex networks and the
challenges when extracting data from complex networks are discussed first. Then, the reason for choosing
Sina Weibo as the data source is given. After that, the methods for data gathering are introduced and the
techniques for data sampling and data clean-up are discussed. Over 1 million users and hundreds of
millions of social relations between them were extracted from Sina Weibo using the methods proposed in
this paper.
AN INTEGRATED RANKING ALGORITHM FOR EFFICIENT INFORMATION COMPUTING IN SOCIAL...ijwscjournal
Social networks have ensured the expanding disproportion between the face of WWW stored traditionally in search engine repositories and the actual ever changing face of Web. Exponential growth of web users and the ease with which they can upload contents on web highlights the need of content controls on material published on the web. As definition of search is changing, socially-enhanced interactive search methodologies are the need of the hour. Ranking is pivotal for efficient web search as the search performance mainly depends upon the ranking results. In this paper new integrated ranking model based on fused rank of web object based on popularity factor earned over only valid interlinks from multiple social forums is proposed. This model identifies relationships between web objects in separate social networks based on the object inheritance graph. Experimental study indicates the effectiveness of proposed Fusion based ranking algorithm in terms of better search results.
A COMPREHENSIVE STUDY ON DATA EXTRACTION IN SINA WEIBOijaia
With the rapid growth of users in social networking services, data is generated in thousands of terabytes
every day. Practical frameworks for data extraction from social networking sites have not been well
investigated yet. In this paper, a methodology for data extraction with respect to Sina Weibo is discussed.
In order to design a proper method for data extraction, the properties of complex networks and the
challenges when extracting data from complex networks are discussed first. Then, the reason for choosing
Sina Weibo as the data source is given. After that, the methods for data gathering are introduced and the
techniques for data sampling and data clean-up are discussed. Over 1 million users and hundreds of
millions of social relations between them were extracted from Sina Weibo using the methods proposed in
this paper.
AN INTEGRATED RANKING ALGORITHM FOR EFFICIENT INFORMATION COMPUTING IN SOCIAL...ijwscjournal
Social networks have ensured the expanding disproportion between the face of WWW stored traditionally in search engine repositories and the actual ever changing face of Web. Exponential growth of web users and the ease with which they can upload contents on web highlights the need of content controls on material published on the web. As definition of search is changing, socially-enhanced interactive search methodologies are the need of the hour. Ranking is pivotal for efficient web search as the search performance mainly depends upon the ranking results. In this paper new integrated ranking model based on fused rank of web object based on popularity factor earned over only valid interlinks from multiple social forums is proposed. This model identifies relationships between web objects in separate social networks based on the object inheritance graph. Experimental study indicates the effectiveness of proposed Fusion based ranking algorithm in terms of better search results.
UNIT II MODELING AND VISUALIZATION
Visualizing Online Social Networks - A Taxonomy of Visualizations - Graph Representation -
Centrality- Clustering - Node-Edge Diagrams - Visualizing Social Networks with Matrix-Based
Representations- Node-Link Diagrams - Hybrid Representations - Modelling and aggregating
social network data – Random Walks and their Applications –Use of Hadoop and Map Reduce -
Ontological representation of social individuals and relationships.
Prior empirical and theoretical work has discussed the role of dominant search engine plays in the function of information gatekeeping on the Web, and there are reports on the high ranking of Wikipedia website among the search engine result pages (SERP). However, little research has been conducted on non-Google search engines and non-English versions of user-generated encyclopedias. This paper proposes a method to quantify the “display” gatekeeping differences of the SERP ranking and presents findings based on the Chinese SERP data. Based on 2,500 mainly-Chinese-language search queries, the data set includes the SERP outcome of four Chinese-speaking regions (mainland China, Singapore, Hong Kong and Taiwan) provided by three major search engines (Baidu, and Google and Yahoo), covering over 97% of the search engine market in each region. The findings, analysed and visualized using network analysis techniques, demonstrate the followings: major user-generated encyclopedias are among the most visible; localization factors matter (certain search engine variants produce the most divergent outcomes, especially mainland Chinese ones). The indicated strong effects of “network gatekeeping” by search engines also suggest similar dynamics inside user-generated encyclopedias.
The “use” of an electronic resource from a social network analysis perspectiveMarie Kennedy
Presented at QQML 2013: Qualitative and Quantitative Methods in Libraries International Conference. Rome, Italy.
Academic libraries in the United States typically reference proxy server and/or COUNTER statistics to describe the usage of their electronic resources, but we know that a “use” is arguably more than a resource accessed or downloaded. This article employs social network analysis to bridge the typical ways of talking about usage statistics, to provide a context-specific perspective about the mediated use of electronic resources. The article reports on an analysis of data gathered at the Loyola Marymount University (Los Angeles, California) using traditional statistics as well as library reference encounters with patrons during which an electronic resource is mentioned. We use the reference encounters in a social network analysis to examine the relationship between a patron, a librarian, and an electronic resource to more fully describe the use of the resource. This research provides a conceptual model for comparison between traditional COUNTER statistics, proxy server statistics, and the social network analysis perspective. We transform qualitative data into quantitative data in order to develop a grounded theory about the mediated access to library electronic resources.
Mining and Analyzing Academic Social NetworksEditor IJCATR
Academics establish relationships by way of various interactions like jointly authoring a research paper or report, jointly
supervising a thesis, working jointly on a project, etc. Some of these relationships are ubiquitous whereas other are hard to keep track
of. Of all types of possible academic and research collaborations, co-authorship is best documented. In this paper we analyze the coauthorship
based academic social networks of computer science engineering departments of Indian Institutes of Technology (IITs) as
evidenced from their research publications produced during 2011 and 2015. We use social network analysis metrics to study the
collaboration networks in four leading IITs. From experimental results it can be concluded that IIT Delhi and IIT Kharagpur have a
close knit collaboration network whereas the collaboration network of IIT Kanpur and IIT Madras is fragmented. However, the
collaboration networks of all the four IITs exhibit similar network properties as expected from any other collaboration network
R. Zafarani, M. A. Abbasi, and H. Liu, Social Media Mining: An Introduction, Cambridge University Press, 2014.
Free book and slides at http://socialmediamining.info/
Characterizing Data and Software for Social Science ResearchMicah Altman
This presentation describes the landscape of data and software use across the social sciences in terms of the abstract dimensions of data and data use. It then examines three use cases.
Presentation for DASPOS < https://daspos.crc.nd.edu/index.php/workshops/workshop-2 > Workshop at JCDL.
Fuzzy AndANN Based Mining Approach Testing For Social Network AnalysisIJERA Editor
Fast and Appropriate Social Network Analysis (SNA) tools ,techniques, are required to collect and classify
opinion scores on social networksites , as a grouping on wrong opinion may create problems for a society or
country . Social Network Analysis (SNA) is popular means for researcher as the number of users and groups
increasing day by day on that social sites , and a large group may influence other.In this paper, we
recommendhybrid model of opinion recommendation systems, for single user and for collective community
respectively, formed on social liking and influence network theory. By collecting thedata of user social networks
and preferenceslike, we designed aimproved hybrid prototype to imitate the social influence by like and sharing
the information among groups.The significance of this paper to analyze the suitability of ANN and Fuzzy sets
method in a hybrid manner for social web sites classifications, First, we intend to use Artificial Neural
Network(ANN)techniques in social media data classification by using some contemporary methods different
than the conventional methods of statistics and data analysis, in next we want to propagate the fuzzy approach
as a way to overcome the uncertainity that is always present in social media analysis . We give a brief overview
of the main ideas and recent results of social networks analysis , and we point to relationships between the two
social network analysis and classification approaches .This researchsuggests a hybrid classification model build
on fuzzy and artificial neural network (HFANN). Information Gain and three popular social sites are used to
collect information depicting features that are then used to train and test the proposed methods . This neoteric
approach combines the advantages of ANN and Fuzzy sets in classification accuracy with utilizing social data
and knowledge base available in the hate lexicons.
Adaptive Collective Systems - Herding black sheepFoCAS Initiative
This book is about understanding, designing, controlling, and governing adaptive collective systems. It is intended for readers from master's students to Ph.D. students, from engineers to decision makers, and anyone else who is interested in understanding how technologies are changing the way we think and live.
The authors are academics working in various areas of a new rising field: adaptive collective systems.
Stuart Anderson (The University of Edinburgh, United Kingdom)
Nicolas Bredeche (Université Pierre et Marie Curie, France)
A.E. Eiben (VU University Amsterdam, Netherlands)
George Kampis (DFKI, Germany)
Maarten van Steen (VU University Amsterdam, Netherlands)
Book Sprint collaborative writing session facilitator: Adam Hyde
Editor: Sandra Sarala
Designer: Henrik van Leeuwen
These are my slides from a presentation to the Chicago R User Group on Oct 3, 2012. It covers how to use R and Gephi to visualize a map of influence in the history of philosophy.
More detail is available on the Design & Analytics Blog.
UNIT II MODELING AND VISUALIZATION
Visualizing Online Social Networks - A Taxonomy of Visualizations - Graph Representation -
Centrality- Clustering - Node-Edge Diagrams - Visualizing Social Networks with Matrix-Based
Representations- Node-Link Diagrams - Hybrid Representations - Modelling and aggregating
social network data – Random Walks and their Applications –Use of Hadoop and Map Reduce -
Ontological representation of social individuals and relationships.
Prior empirical and theoretical work has discussed the role of dominant search engine plays in the function of information gatekeeping on the Web, and there are reports on the high ranking of Wikipedia website among the search engine result pages (SERP). However, little research has been conducted on non-Google search engines and non-English versions of user-generated encyclopedias. This paper proposes a method to quantify the “display” gatekeeping differences of the SERP ranking and presents findings based on the Chinese SERP data. Based on 2,500 mainly-Chinese-language search queries, the data set includes the SERP outcome of four Chinese-speaking regions (mainland China, Singapore, Hong Kong and Taiwan) provided by three major search engines (Baidu, and Google and Yahoo), covering over 97% of the search engine market in each region. The findings, analysed and visualized using network analysis techniques, demonstrate the followings: major user-generated encyclopedias are among the most visible; localization factors matter (certain search engine variants produce the most divergent outcomes, especially mainland Chinese ones). The indicated strong effects of “network gatekeeping” by search engines also suggest similar dynamics inside user-generated encyclopedias.
The “use” of an electronic resource from a social network analysis perspectiveMarie Kennedy
Presented at QQML 2013: Qualitative and Quantitative Methods in Libraries International Conference. Rome, Italy.
Academic libraries in the United States typically reference proxy server and/or COUNTER statistics to describe the usage of their electronic resources, but we know that a “use” is arguably more than a resource accessed or downloaded. This article employs social network analysis to bridge the typical ways of talking about usage statistics, to provide a context-specific perspective about the mediated use of electronic resources. The article reports on an analysis of data gathered at the Loyola Marymount University (Los Angeles, California) using traditional statistics as well as library reference encounters with patrons during which an electronic resource is mentioned. We use the reference encounters in a social network analysis to examine the relationship between a patron, a librarian, and an electronic resource to more fully describe the use of the resource. This research provides a conceptual model for comparison between traditional COUNTER statistics, proxy server statistics, and the social network analysis perspective. We transform qualitative data into quantitative data in order to develop a grounded theory about the mediated access to library electronic resources.
Mining and Analyzing Academic Social NetworksEditor IJCATR
Academics establish relationships by way of various interactions like jointly authoring a research paper or report, jointly
supervising a thesis, working jointly on a project, etc. Some of these relationships are ubiquitous whereas other are hard to keep track
of. Of all types of possible academic and research collaborations, co-authorship is best documented. In this paper we analyze the coauthorship
based academic social networks of computer science engineering departments of Indian Institutes of Technology (IITs) as
evidenced from their research publications produced during 2011 and 2015. We use social network analysis metrics to study the
collaboration networks in four leading IITs. From experimental results it can be concluded that IIT Delhi and IIT Kharagpur have a
close knit collaboration network whereas the collaboration network of IIT Kanpur and IIT Madras is fragmented. However, the
collaboration networks of all the four IITs exhibit similar network properties as expected from any other collaboration network
R. Zafarani, M. A. Abbasi, and H. Liu, Social Media Mining: An Introduction, Cambridge University Press, 2014.
Free book and slides at http://socialmediamining.info/
Characterizing Data and Software for Social Science ResearchMicah Altman
This presentation describes the landscape of data and software use across the social sciences in terms of the abstract dimensions of data and data use. It then examines three use cases.
Presentation for DASPOS < https://daspos.crc.nd.edu/index.php/workshops/workshop-2 > Workshop at JCDL.
Fuzzy AndANN Based Mining Approach Testing For Social Network AnalysisIJERA Editor
Fast and Appropriate Social Network Analysis (SNA) tools ,techniques, are required to collect and classify
opinion scores on social networksites , as a grouping on wrong opinion may create problems for a society or
country . Social Network Analysis (SNA) is popular means for researcher as the number of users and groups
increasing day by day on that social sites , and a large group may influence other.In this paper, we
recommendhybrid model of opinion recommendation systems, for single user and for collective community
respectively, formed on social liking and influence network theory. By collecting thedata of user social networks
and preferenceslike, we designed aimproved hybrid prototype to imitate the social influence by like and sharing
the information among groups.The significance of this paper to analyze the suitability of ANN and Fuzzy sets
method in a hybrid manner for social web sites classifications, First, we intend to use Artificial Neural
Network(ANN)techniques in social media data classification by using some contemporary methods different
than the conventional methods of statistics and data analysis, in next we want to propagate the fuzzy approach
as a way to overcome the uncertainity that is always present in social media analysis . We give a brief overview
of the main ideas and recent results of social networks analysis , and we point to relationships between the two
social network analysis and classification approaches .This researchsuggests a hybrid classification model build
on fuzzy and artificial neural network (HFANN). Information Gain and three popular social sites are used to
collect information depicting features that are then used to train and test the proposed methods . This neoteric
approach combines the advantages of ANN and Fuzzy sets in classification accuracy with utilizing social data
and knowledge base available in the hate lexicons.
Adaptive Collective Systems - Herding black sheepFoCAS Initiative
This book is about understanding, designing, controlling, and governing adaptive collective systems. It is intended for readers from master's students to Ph.D. students, from engineers to decision makers, and anyone else who is interested in understanding how technologies are changing the way we think and live.
The authors are academics working in various areas of a new rising field: adaptive collective systems.
Stuart Anderson (The University of Edinburgh, United Kingdom)
Nicolas Bredeche (Université Pierre et Marie Curie, France)
A.E. Eiben (VU University Amsterdam, Netherlands)
George Kampis (DFKI, Germany)
Maarten van Steen (VU University Amsterdam, Netherlands)
Book Sprint collaborative writing session facilitator: Adam Hyde
Editor: Sandra Sarala
Designer: Henrik van Leeuwen
These are my slides from a presentation to the Chicago R User Group on Oct 3, 2012. It covers how to use R and Gephi to visualize a map of influence in the history of philosophy.
More detail is available on the Design & Analytics Blog.
These are the slides for a tutorial talk about "multilayer networks" that I gave at NetSci 2014.
I walk people through a review article that I wrote with my PLEXMATH collaborators: http://comnet.oxfordjournals.org/content/2/3/203
Online conversations (and even offline ones) are, deep down, networks. But how to visualize network data so that they make sense to non-network scientists?
Presentation at the second CATALYST consortium meeting.
Gephi Plugin Devleoper Workshop, October 6, 2011 in Mountain View, California.
Presentation of Gephi's architecture and the different types of plugins that can be written with examples. Details about Gephi's API, code examples and best practices are presented. The Gephi Toolkit is also covered.
Revision of Previous Show on SNA and Introduction to Tools
The Language of Networks
Introduction to Social Network Analysis/ Cases
Tools for Analyzing social networks, including graphing Facebook, LinkedIn, and Twitter networks
Questions Numériques 2014/2015 : Les ControversesFing
En quelques années, le numérique a acquis un statut consensuel : chacun reconnaît son importance dans nos vies quotidiennes. Nous l’avons intégré comme une composante certaine de l’avenir. Il nous semble néanmoins urgent de s’interroger sur les enjeux sociétaux des mutations numériques.
Les controverses au cœur de ce cahier de prospective constituent un outil stratégique, pour prendre aujourd’hui les décisions qui engageront les acteurs décideurs demain.
Les Mooc annoncent-ils vraiment une révolution éducative ? Les Big Data créent-elles plus de problèmes qu’elles n’en résolvent ? Le numérique crée-t-il de l’emploi ? détruit-il le lien social ? La démocratisation de la conception-fabrication produit-elle une « nouvelle révolution industrielle » ?…
Gamification - Defining, Designing and Using itZac Fitz-Walter
A presentation that describes the concept of gamification, it's roots, design and application. Minimal words, lots of pics and lots of fun to present. :)
Make sure to sign up to my weekly gamification newsletter: http://gamificationweekly.com
Social Network Analysis & an Introduction to ToolsPatti Anklam
This presentation was delivered as part of an intense knowledge management curriculum. It covers the basics of network analysis and then goes into the different types of tool that support analyzing networks.
Web.gov: Observations About, Strategies Relating To, and Lessons Learned from...UXPA International
UXPA 2013 Conference - Wednesday, July 10, 2013, 11:00am – 12:00 pm by Jeffrey Ryan Pass
The Obama Administration’s 2012 Digital Government Strategy set a high bar for Federal websites, calling for the creation of “information-centric” and “customer-centric” sites and mandating “citizen-engagement.”
This presentation provides an overview of the Digital Government Strategy, discusses how it came into being, and provides specific examples of recent and ongoing work in support of the strategy from a number of federal agencies. It also considers how user experience (UX) professionals can advocate for the Digital Government Strategy and how they can put its tenants to work to better serve their clients (Federal or otherwise) and, most important, the digital content users.
Full Title: Web.gov: Observations About, Strategies Relating To, and Lessons Learned from the US Digital Government Strategy (and how they apply to the Broader UX Community)
Short Description:
The Obama Administration’s 2012 Digital Government Strategy set a high bar for Federal websites, calling for the creation of “information-centric” and “customer-centric” sites and mandating “citizen-engagement.”
This presentation provides an overview of the Digital Government Strategy, discusses how it came into being, and provides specific examples of recent and ongoing work in support of the strategy from a number of federal agencies. It also considers how user experience (UX) professionals can advocate for the Digital Government Strategy and how they can put its tenants to work to better serve their clients (Federal or otherwise) and, most important, the digital content users.
ONS Local has been established by the Office for National Statistics (ONS) to support evidence-based decision-making at the local level. We aim to host insightful events that connect our users with exciting developments happening in subnational statistics and analysis at the ONS and across other organisations.
Have you ever wondered which local authorities are similar to each other? This presentation discusses cluster analysis ONS has published to draw insight into which local authorities are performing in a similar way against key policy themes, promoting greater joined up working between local authorities with similar characteristics to address common problems they face. Our analysis also provides local authorities with control groups for investigating the impact of policy interventions.
In this webinar, we will cover the methods used to create our outputs, demonstrate some of our findings in our interactive visualisation tool and present information on our future plans to expand on this work.
This event is open to all, however we anticipate it will be of most interest to anyone working at a local level, or with data on the policy themes of economy, transport connectivity, education, skills, health and wellbeing.
If you have any questions, please contact ons.local@ons.gov.uk
So you want to be a GOV UXer: A(n updated) primer for anyone interested in d...Jeffrey Ryan Pass
UPDATED for 2023.
Working for the US Federal Government (as an employee or contractor) is a unique experience. This is especially true for UXers.
This presentation provides an overview of the peculiarities, challenges, and rewards of working as a GOV UXer and offers advice for getting started, succeeding, and spreading the culture of good UX (aka CX or citizen experience). The presentation includes:
– GOV UX stats that might surprise you
– A brief history of US Federal GOV UX / rules, regs, and limitations affecting UX work
– Agencies, actors, and influencers to know
– Federal web culture fundamentals
– Citizen engagement goals and techniques
– Usability testing rules, regs, and workarounds
– Resources and communities for GOV UXers
1 PHY 241 Fall 2018 PHY 241 Lab 7- Momentum is Conserved.docxoswald1horne84988
1
PHY 241 Fall 2018
PHY 241 Lab 7- Momentum is Conserved
Introduction:
Momentum is a vector quantity which is measured by taking the product of an objects mass and
velocity,
𝑝 = 𝑚�⃗�. (1)
Much like energy, the concept of momentum is useful because we have a law which guarantees that the
momentum of an appropriate system is conserved.
“The total amount of momentum in a system is a constant unless momentum is transferred
through the system boundary by an Impulse.”
Where an impulse is an external force which acts on a system over time,
𝐼 = ∫ 𝐹𝑒𝑥𝑡⃗⃗ ⃗⃗ ⃗⃗ ⃗⃗ 𝑑𝑡.
Equipment:
Two CBR 2- connected directly to a computer using USB cables
Various collision carts
Mass blocks for carts
2 m track
Bubble level
Computer with Logger Pro or Logger Lite and Excel.
Triple beam balance scale.
Procedure:
1) Design a procedure to collect the information you need to measure the momentum of two
carts simultaneously. WARNING: Occasionally, the clicks from your two different CBRs will
interfere with each other and give incorrect data. Your group should develop criteria to
determine when data is invalid and a response.
2) Generate a plot of the momentum of each cart as well as the total momentum similar to
“Carts’ Momenta.” Notice you must correct for the fact that the two different CBRs are
using different coordinate systems.
2
PHY 241 Fall 2018
3) Similarly, generate a plot of the kinetic energy of each cart as well as the total kinetic
energy.
4) This should allow you to make a single plot containing both the Kinetic Energy and the
Momenta for the same collision. Notice you will need to let Excel know that Energy needs
to be plotted on a “Secondary Axis” because these two quantities have different units.
1 1.2 1.4 1.6 1.8 2
E
n
e
rg
y
(
J)
M
o
m
e
n
tu
m
(
k
g
m
/s
)
Time (s)
Energy and Momentum
Total Momentum Total Kinetic Energy
1 1.2 1.4 1.6 1.8 2
M
o
m
e
n
tu
m
(
k
g
m
/s
)
Time (s)
Carts' Momenta
Cart 1 Cart 2 Total Momentum
1 1.2 1.4 1.6 1.8 2
E
n
e
rg
y
(
J)
Time (s)
Carts' Energies
Cart 1 Cart 2 Total Kinetic Energy
3
PHY 241 Fall 2018
5) At this point there are a few questions that that arise from the Energy and Momentum
graph above. To
A) DA- Is the behavior of the Energy and Momentum graph unique to the specific details of
the collision. Collect energy and momentum data for at least four different collisions
(magnet/spring/Velcro, different mass carts, etc.) and find a way to visualize all this data
so you can qualitatively compare and contrast features you see in the data.
B) Researcher- Choose a single trial to investigate momentum carefully. Is momentum
conserved? Measure the Impulse generated by force(s) on your system and see if you
can account for any changes in momentum you observed. Be as quantitative as
possible.
C) PI- Choose a single trial to investigate energy carefully. Energy appears to
International Journal of Engineering Research and Development (IJERD)IJERD Editor
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
WATEF 2018 신년 세미나
안녕하십니까?
이번 세미나는 인적교류 및 정보교류와 더불어 유연한 관계형성을 목적으로
소규모의 사랑방 형식으로 진행하고자 하오니 많은 참석바랍니다.
□ 일 시 : 2018. 2. 2. (금) 오후 3:30~5:30
□ 장 소 : 스마트미디어센터(대구 동구 동대구로 489번지 대구무역회관 2층)
□ 발표주제
【좌장】 백승대(영남대)
【세션1】 성폭력에 대한 언론 보도 양상과 사회적 인식 탐구
- 발표자: 임연수(홍익대)
- 토론자: 석민(매일신문사), 남인용(부경대), 윤희웅(오피니언라이브)
【세션2】 지역의 미래전략에 미치는 미래준비 요인에 관한 연구
- 발표자: 송영조(한국정보화진흥원)
- 토론자: 이정미(대구경북연구원), 안중곤(대구시청), 오경묵(한국경제신문)
WATEF 2018 신년 세미나
안녕하십니까?
이번 세미나는 인적교류 및 정보교류와 더불어 유연한 관계형성을 목적으로
소규모의 사랑방 형식으로 진행하고자 하오니 많은 참석바랍니다.
□ 일 시 : 2018. 2. 2. (금) 오후 3:30~5:30
□ 장 소 : 스마트미디어센터(대구 동구 동대구로 489번지 대구무역회관 2층)
□ 발표주제
【좌장】 백승대(영남대)
【세션1】 성폭력에 대한 언론 보도 양상과 사회적 인식 탐구
- 발표자: 임연수(홍익대)
- 토론자: 석민(매일신문사), 남인용(부경대), 윤희웅(오피니언라이브)
【세션2】 지역의 미래전략에 미치는 미래준비 요인에 관한 연구
- 발표자: 송영조(한국정보화진흥원)
- 토론자: 이정미(대구경북연구원), 안중곤(대구시청), 김윤영(한국패션산업연구원)
Another Interdisciplinary Transformation: Beyond an Area-studies JournalHan Woo PARK
Journal of Contemporary Eastern Asia (ISSN 2383-9449) is a refereed biannual journal that takes a lead on a new scholarship in Asia. In the past, the JCEA was dedicated to the study of current political, social and economic trends in East and Southeast Asia. But now, the JCEA finds unique aspects of Asian scholarship by expanding its scope to (socio-technical) convergence and future (network) studies. The JCEA editors are working very hard to boost the scholarly presence of new Asian scholarship around the world and secure its reputation as an emerging world-class publishing outlet. The editors welcome manuscripts based on original research or significant reexamination of existing literature.
암호화폐에 대해 적극 규제 입장을 보이는 정부에 대해 아쉬움을 드러내며 청와대에 규제 반대 청원을 낸 영남대 사이버감성연구소 박한우 교수. 국내 빅 데이터 연구 권위자로 잘 알려진 그는 지금까지 100여 편에 달하는 관련 논문을 게재하며 빅 데이터를 통해 사회를 해석하고 있는 학자다. 게다가 빅 데이터를 활용한 여론조사 특허까지 획득하며 빅 데이터 연구의 체계를 잡아가고 있다. 그런 그가 암호화폐 규제 반대에 대한 이유와 블록체인 기술과 정부가 해야 할 일에 대해 의견을 들었다.
1. 청와대에 가상화폐 규제를 반대하는 청원을 낸 것으로 알고 있다. 가상화폐 규제에 반대 하는 이유는 무엇인가
가상화페는 오역된 단어이다. 엄격히 말하면, 암호화폐가 맞다. 세계 암호화페 시장은 기축통화인 비트코인 그리고 이더리움 등 알트코인을 포함하면 약 700여 개가 등록되어 있다. 앞으로 3,000여 개가 등록 준비 중이다. 우리나라도 미래자산으로서 비트코인 거래가 활성화되고 있다. 현재 암호화폐 시장에 특히 한국시장에 유독 과열이 심한 건 맞다고 본다. 상징적인 가격대인 1만 달러를 넘으면서 우리나라 뿐 아니라 전 세계 각국에서도 고민이 커져가고 있는 것도 사실이다. 그러나 문재인 정부가 이러한 트렌드에 제대로 부응하려면, 암호화폐 분야의 세계적 동향과 국내 현황 간 미스매치를 언급하며 정책적 지원이 필요함을 역설해야지 규제를 말할 단계가 아니다.
close
2. 가상화폐 규제 시 어떤 문제점이 발생할 것이라 예상되는가
신호등 효과가 발생할 것이다. 청색등에서 적색으로 바뀌기 전 황색등 기간에 더 많은 부작용이 생겨날 것이다. 일확천금의 마지막 기회라고 생각해서 시장이 더 불안정해질 것이며, 아노미 상태가 될 것이다. 규제의 근거로서 청소년과 주부의 무분별한 투기행태를 언급하는 것은 적폐대상인 탁상행정을 다시 보여주는 것이다. 2018년 중등 교육과정에 코딩수업이 정규과정으로 포함된다. 코딩수업에서 우리의 청소년이 꿈꾸어야 할 직업은 무엇인가? 그것은 바로 글로벌 경쟁력을 지닌 암호화폐를 개발하는 것이다. 이더리움은 러시아 프로그래머인 비탈릭 부테린이 개발했다. 고학력의 경력단절 여성들이 육아와 가사를 병행하면서 할 수 있는 무엇인가? 모바일 금융거래사로서 새로운 사회적 성장동력이 되는 것이다. 상황이 이러함에도 불구하고, 새로운 정부는 기술의 편의성과 위험성 이슈를 운운하는 구태를 드러내고 있다, 기능이 겹치거나 기술이 완성되지 못한 암호화폐는 자연도태 되게 되어있다. 정부에서도 무조건적인 투자, 투기라기보다는 위험성을 제대로 알려주면서 암호화폐의 건전한 발전을 위한 제도를 만들어 나가는 게 필요하다고 본다. 암호화폐나 블록체인이 우리 국가를 어떻게 더 나은 사회로 만들 수 있는지에 대해 새로운 정책을 만들고 그 정책에 따라 규제를 연결지어 나오는게 더 올바르지 않을까 생각한다.
close
3. 암호화폐와 블록체인 기술의 가능성에 대해 어떻게 보고있는가
미국 시카고 선물시장에서 비트코인 거래가 개시되었다. 이것이 암호화폐의 제도권 진입을 공식화하지는 않지만, 신기루처럼 허구는 아닐 수 있다는 것을 드러낸다. 2018년에는 비트코인 거래의 대중화와 캐쉬리스 모바일 지불결제의 확산될 것이다. 또한 비트코인을 이용한 개인-개인(P2P) 사이트가 생겨나면서 중고물품과 디지털콘텐츠 거래시스템 활용논의가 중요하게 등장할 것이다. 또한 블록체인의 질적 성장을 통해 탈중앙화를 가속화 시키고 국가가 분산, 투명, 협력 되는 생태계를 만들어 내는 기회를 삼을 수 있으리라 생각한다. 4차산업 혁명에서 가장 핵심이 되는 기술이 공정성과 신뢰성을 가진 연결 융합 플랫폼을 구현하는 것이라고 본다.
4. 정부는 블록체인 기술 발전을 위해 어떤 역할을 해야 한다고 생각하는가
블록체인 기술이 발전하기 위해서는 암호화폐가 반드시 필요하다. 암호화폐와 블록체인은 한 몸이라 보면 된다. 암호화폐에 심각한 규제를 가하기 시작하면 블록체인 기술을 통해 4차 산업을 육성하는 것은 불가능하다고 볼 수 있다.
비트코인 광풍의 이면에 대기업에서 운영하는 암호화폐 거래소의 사회적 책임의식 부재와 이용자 미보호가 심각한 문제로 등장하는 것이 핵심 트렌드임을 깨달아야 한다. 나아가, 소득이 있는 곳에 세금이 있다는 원칙을 지키면 된다. 거래소 개설 이후의 소득에 대해서는 세금을 부과해야 한다. 하지만 주택임대사업자처럼 일정금액 이상은 부가세를 면제하여 개미투자자들을 보호하면 된다. 이것은 문재인 정부가 추구하는 정의로운 나라와 궤를 같이 하는 것이다.
나아가 블록체인에 대한 세계적 관심이 더 높아지면서 관련 원천기술의 확보방안이 주요 이슈로 부상될 것이다. Lisk coin은 독일 베를린에 오미세고는 태국 방콕, 라이트코인은 싱가폴에 본부를 두고 있다
장성혁기자 jsh0529@msnet.co.kr
KISTI-WATEF-BK21Plus-사이버감성연구소 2017 동계세미나 자료집Han Woo PARK
WATEF 2017 동계세미나 및 정기총회 개최
1. 행사 개요
o 목 적 : 데이터와 콘텐츠 기반 과학기술의 공공성 회복방향에 대한 전문가 의견
공유
o 일 시 : 2017. 11.30(목)
o 장 소 : KISTI(한국과학기술정보연구원) 대전 본원 별관 회의실
o 참석자 : WATEF 회원 및 KISTI 관련자 등 50여명
o 주 관 : WATEF
o 주 최 : WATEF, KISTI(한국과학기술정보연구원), 영남대 BK플러스사업단 사물
인터넷 빅데이터 지능서비스 사업팀, 영남대사이버감성연구소(빅데이터
융복합센터)
http://watef.org/home/bbs/board.php?bo_table=notice&wr_id=73
학회원 여러분 위와같이 WATEF 2017 동계세미나를 KISTI 대전본원 회의실에서 개최합니다. 많은 회원분들의 참석 바랍니다.
사전등록신청은 지난번 하계세미나처럼 온라인으로 간편하게 접수 가능합니다.
https://goo.gl/forms/FPLfxGQ5ZeOdh6A63 <- 사전등록신청 링크
Global mapping of artificial intelligence in Google and Google ScholarHan Woo PARK
Omar, M., Mehmood, A., Choi, G.S., Park, H.W.@ (2017 Online First). Global mapping of artificial intelligence in Google and Google Scholar. Scientometrics.
https://link.springer.com/article/10.1007%2Fs11192-017-2534-4
#인공지능 분야의 국가별 현황과 전망을 #웹보메트릭스 #빅데이터 #구글데이터 이용해서 세계지도를 그렸습니다.
박한우 영어 이력서 Curriculum vitae 경희대 행사 제출용Han Woo PARK
Full Prof. Dr. Han Woo PARK, http://www.hanpark.net https://www.slideshare.net/hanpark
(BA-HUFS, MA-Seoul Nat'l Univ. PhD-SUNY Buffalo)
Dept of Media & Communication, Interdisciplinary Program of Digital Convergence Business, YeungNam University, 214-1, Dae-dong, Gyeongsan-si, Gyeongsangbuk-do, South Korea, Zip Code 712-749
Editor-In-Chief of Journal of Contemporary Eastern Asia, https://jceasia.org/
Guest Editors of Social Science Computer Review, Journal of Computer-Mediated Communication, Asian Journal of Communication, Scientometrics, Quality & Quantity, Technological Forecasting & Social Change
Editorial Boards of Scientometrics, Quality & Quantity, International Journal of Internet Science, Big Data & Society, CollNet Journal of Scientometrics & Information Management, Knowledge Economy, International Journal of Technology Management & Sustainable Development, Social Media & Society, Triple Helix - A Journal of University-Industry-Government Innovation and Entrepreneurship, Technological Forecasting & Social Change, Journal of Data & Information Science, Scholarly Metrics and Analytics (a specialty of Frontiers in Library and Information Science)
Director of Cyber Emotions Research Institute
President of WATEF (World Association for Triple Helix & Future Strategy Studies,
Formerly, Asia Triple Helix Society)
Formerly, Directors of World Class University Webometrics Institute and TEDxPalgong ,Visiting Scholar of Oxford Internet Institute https://www.oii.ox.ac.uk/people/han-woo-park/ Research Associate of Royal Netherland Academy (NIWI-KNAW http://virtualknowledgestudio.nl/people/former-vks-members/
Twitter network map of #ACPC2017 1st day using NodeXLHan Woo PARK
The Asian Conference for Political Communication 2017 is a biennial conference spearheaded by the Media Programme Asia of Konrad-Adenauer-Stiftung. Join fellow influencers in academia, politics and government on this special occasion. Talk about challenges on social media, discuss the odds and threats of #twiplomacy, analyze the phenomena of rising populism and watch the hottest tools for e-campaigning.
2016년 촛불집회는 과거와 달리 수도권뿐만 아니라 지방에서도 전개되었다. 그러나 서울 광화
문 광장 이외에서 진행된 촛불집회에 대한 사회적 관심은 그 중요성에 비해서 주목받지 못했다.
이 연구는 지방의 촛불집회 특히, 대통령의 정치적 고향인 대구·경북(TK) 촛불집회에 주목하였
다. 본 논문은 페이스북에 남겨진 데이터를 이용해 촛불집회에 나타난 TK지역 여론의 행위자와
댓글의 내용을 검토한다. 첫째, 페이지의 운영주체에 따라 페이스북 이용자 행위의 차이가 있는
지 살펴보았다. 둘째, 집회유형에 따른 댓글의 의견과 그 전개양상이 다른지 살펴보았다. 분석방
법으로 이용자 반응분석, 연결망분석(social network analysis), 의미망분석이 사용되었다. 연구결과,
페이스북 이용자들의 관심도, 참여율, 응집도는 전통 미디어에서 운영한 페이지보다 시민참여형
UCC(user created content) 페이지에서 높게 나타났다. 집회유형으로 보면, 촛불집회 댓글들과 비
교해 ‘박사모’ 반응에서 노인폄하 단어 등 부정적 단어들이 더 자주 출현했다. 이 연구는 페이스
북 댓글 데이터를 이용해서 기존에 자주 수행된 마케팅과 선거캠페인을 넘어서 새로운 연구방향
을 제시했다는 점에서 학술적 의미뿐만 아니라 사회적 가치가 있다.
세계산학관협력총회 http://www.watef.org 패널을 공지합니다.
토론자로 참여가능한 분도 모집합니다. 많은 관심을 부탁드려요.
2017 Triple Helix Conference Special Issue Session http://www.triplehelix-korea.org/
Theme (주제): Measuring Triple Helix Synergies and Innovations using Scientometric, Technometric, Informetric, Webometric, and Altmetric Data
9월 15일 금요일 16:45 - 18:15 장소: 대구엑스코
페이스북 라이브 생중계: 서인수 (즐거운 사물인터넷 대표)
Organizers
Mi Young Chong (Univ. of North Texas, USA) miyoungchong@my.unt.edu
Han Woo Park (Yeungnam University, South Korea)
발표자: 김도훈, Brandon Moore, 윤정원
Presenter: Leo Kim
Title: From Institution to Individual: Data-Based Reflection of Triple-Helix Operation in South Korea
Biography: Leo Kim is the CEO of Ars Praxia. He graduated from LSE (Methodology, Master) and University of Sussex (Science and Technology Studies, PhD). He has been developing the methodology of semantic network analysis and has a professional background in innovation studies and unstructured data analysis.
Presenter: Brandon Moore
Title: Improving open data accessibility: Using domain driven design and microservice architecture to create user friendly open data systems
Biography: Brandon Moore is a solutions architect for Nationstar Mortgage LLC. He has 20 years experience as a software engineer and is currently the lead architect for a new reverse mortgage platform. He is also an Information Science PhD student at the University of North Texas. His research interests are text analytics and data mining.
Presenter: Jungwon Yoon
TItle: Triple Helix Dynamics of Technological Innovation Systems in South Korea: A Comparative Analysis
Biography: Jungwon Yoon is a research fellow at Soongsil University in South Korea. She received her Ph.D. in Sociology of Technology and Science from Georgia Institute of Technology, USA. Her areas of expertise are in science and technology studies (STS), including science & technology policy, sociology of sciences, innovation studies, and technology management. Her current research focuses on dynamics of innovation systems in both South and North Korea. Her latest publications include "Triple helix dynamics of South Korea’s innovation system: a network analysis of inter-regional technological collaborations" and "Quintuple helix structure of Sino-Korean research collaboration in science."
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...Neo4j
Leonard Jayamohan, Partner & Generative AI Lead, Deloitte
This keynote will reveal how Deloitte leverages Neo4j’s graph power for groundbreaking digital twin solutions, achieving a staggering 100x performance boost. Discover the essential role knowledge graphs play in successful generative AI implementations. Plus, get an exclusive look at an innovative Neo4j + Generative AI solution Deloitte is developing in-house.
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
Full-RAG: A modern architecture for hyper-personalizationZilliz
Mike Del Balso, CEO & Co-Founder at Tecton, presents "Full RAG," a novel approach to AI recommendation systems, aiming to push beyond the limitations of traditional models through a deep integration of contextual insights and real-time data, leveraging the Retrieval-Augmented Generation architecture. This talk will outline Full RAG's potential to significantly enhance personalization, address engineering challenges such as data management and model training, and introduce data enrichment with reranking as a key solution. Attendees will gain crucial insights into the importance of hyperpersonalization in AI, the capabilities of Full RAG for advanced personalization, and strategies for managing complex data integrations for deploying cutting-edge AI solutions.
20 Comprehensive Checklist of Designing and Developing a WebsitePixlogix Infotech
Dive into the world of Website Designing and Developing with Pixlogix! Looking to create a stunning online presence? Look no further! Our comprehensive checklist covers everything you need to know to craft a website that stands out. From user-friendly design to seamless functionality, we've got you covered. Don't miss out on this invaluable resource! Check out our checklist now at Pixlogix and start your journey towards a captivating online presence today.
Building RAG with self-deployed Milvus vector database and Snowpark Container...Zilliz
This talk will give hands-on advice on building RAG applications with an open-source Milvus database deployed as a docker container. We will also introduce the integration of Milvus with Snowpark Container Services.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Communications Mining Series - Zero to Hero - Session 1DianaGray10
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfMalak Abu Hammad
Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
* What is Vector Search?
* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AIVladimir Iglovikov, Ph.D.
Presented by Vladimir Iglovikov:
- https://www.linkedin.com/in/iglovikov/
- https://x.com/viglovikov
- https://www.instagram.com/ternaus/
This presentation delves into the journey of Albumentations.ai, a highly successful open-source library for data augmentation.
Created out of a necessity for superior performance in Kaggle competitions, Albumentations has grown to become a widely used tool among data scientists and machine learning practitioners.
This case study covers various aspects, including:
People: The contributors and community that have supported Albumentations.
Metrics: The success indicators such as downloads, daily active users, GitHub stars, and financial contributions.
Challenges: The hurdles in monetizing open-source projects and measuring user engagement.
Development Practices: Best practices for creating, maintaining, and scaling open-source libraries, including code hygiene, CI/CD, and fast iteration.
Community Building: Strategies for making adoption easy, iterating quickly, and fostering a vibrant, engaged community.
Marketing: Both online and offline marketing tactics, focusing on real, impactful interactions and collaborations.
Mental Health: Maintaining balance and not feeling pressured by user demands.
Key insights include the importance of automation, making the adoption process seamless, and leveraging offline interactions for marketing. The presentation also emphasizes the need for continuous small improvements and building a friendly, inclusive community that contributes to the project's growth.
Vladimir Iglovikov brings his extensive experience as a Kaggle Grandmaster, ex-Staff ML Engineer at Lyft, sharing valuable lessons and practical advice for anyone looking to enhance the adoption of their open-source projects.
Explore more about Albumentations and join the community at:
GitHub: https://github.com/albumentations-team/albumentations
Website: https://albumentations.ai/
LinkedIn: https://www.linkedin.com/company/100504475
Twitter: https://x.com/albumentations
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!SOFTTECHHUB
As the digital landscape continually evolves, operating systems play a critical role in shaping user experiences and productivity. The launch of Nitrux Linux 3.5.0 marks a significant milestone, offering a robust alternative to traditional systems such as Windows 11. This article delves into the essence of Nitrux Linux 3.5.0, exploring its unique features, advantages, and how it stands as a compelling choice for both casual users and tech enthusiasts.
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!
Disc2013 keynote speakers
1. Exploring the Structure of Government
on the Web
Presentation by Robert Ackland at DISC2013,
12-14 December 2013, Daegu, South Korea
Robert Ackland (Australian National University)
Paul Henman (University of Queensland)
Tim Graham (University of Queensland)
Homepage: https://researchers.anu.edu.au/researchers/ackland-rj
Project: http://voson.anu.edu.au
2. VOSON Project at the ANU (http://voson.anu.edu.au): Teaching,
research and tool development in areas of computational social
science, network science, web science since 2003
2
3. Background
Government use of the Internet has rapidly evolved.
● While this evolution has been examined in terms of the
content, usability and interactivity of sites, the institutional
structure of government on the web is less explored.
● Australian Research Council-funded project titled "The
institutional structure of e-government: a cross-policy,
cross-country comparison" (Henman, Ackland, Margetts)
●
3
4. Overall aims of project
●
Aim 1: Assess whether government hyperlink networks reflect
offline institutional structures
Is e-government facilitating joined-up government or are
jurisdictional boundaries still a significant barrier?
● Whalen (2011) studied the hyperlink structure of the US .gov
domain, assessing correspondence between online structure of
US government and its offline hierarchy.
●
●
Major difference is our project compares the UK and Australia, identifying
both similarities and contrasts in the relationship between institutional
structure and online presence.
4
5. ●
Aim 2: Use hyperlink data to assess “nodality” of government (Hood &
Margetts 2007) – is government at centre of informational networks on
Web?
Nodality affects whether government messages received by the population.
● Web might increase government nodality, but can also decrease nodality,
through increased competition from other information providers (who may
destabilise/confuse/subvert the messages and actions of government).
Example: anti-vaccination lobby groups.
● We ask: is government using the web to enhance its visibility? Are there
differences in nodality across policy domains, countries (AU and UK)?
● Our approach is different to that used by Escher et al. (2006)
●
●
●
Escher et al. focused only on the UK Foreign Office (and US and Australian
counterparts), our analysis includes other sectors of government, allowing crosscountry and cross-sector comparisons
We collect more hyperlink data, allowing us to identify the connection between sites
that link to (or are linked to by) government sites. We can construction of nodality
measures that are different to those used by Escher et al. (e.g. those requiring
complete network data).
5
6. Webometrics (link count analysis)
focus on
egonetworks,
rather than
complete
networks
●
typically only
know attributes
of ego, not
alters
●
6
7. Today – some methodological aspects
Hyperlink network data collection (VOSON)
●
Network reduction techniques
●
Community structure in government
hyperlink networks
●
Coding websites (machine learning)
●
7
9. ●
Manually identified AU and UK government seed pages (typically, entry pages
to government websites):
AU – 88 pages
● UK – 92 pages
●
●
Used the VOSON software (http://voson.anu.edu.au) to construct hyperlink
network data using two stage approach:
●
Stage 1:
●
●
●
Stage 2:
●
●
VOSON in-built crawler crawled the seed sites finding internal pages linked to from the entry
page. Collected outbound links from each of the internal pages and also text content
Bing API was used to find all inbound links to each of the internal pages (including seed page)
Every new page discovered above (i.e. pages that either link to or are linked to by government
web page) was then crawled by VOSON in-built crawler to find connections among these pages
Data collected in 2012
9
11. VOSON 2.0 web
interface works with
Firefox, Chrome, Safari,
iPad
VOSON+NodeXL allows
construction and import
of hyperlink networks
from within NodeXL
11
13. ●
Network size (pages):
AU: 1,517,020 nodes (pages)
● UK: 1,588,757 nodes (pages)
●
●
First major network reduction technique: construct network
of websites rather than pages
VOSON has approach for automatically grouping pages into
“pagegroups”
● e.g for AU, 6694 pages from Australian Taxation office all
included in a single node “ato.gov.au”
●
●
Full network size (pagegroups/sites):
AU: 110665 nodes (pages), 290031 edges
● UK: 109161 nodes (pages), 280580 edges
●
13
14. ●
Gephi map UK network – only showing 30K+ nodes with
indegree+outdegree>1 ...not much analytical potential from this
visualisation...
14
15. ●
In future work we will be investigating
approaches for removing edges to reveal
the “backbone” of UK and AU government
hyperlink networks
●
e.g. Serrano, M., Boguñá, M. and A.
Vespignani (2009): “Extracting the
multiscale backbone of complex weighted
networks,” PNAS, 106(16), 6483-6488.
15
17. Some approaches for 'community'
detection in networks
Modularity maximisation (Lancichinetti &
Fortunato, 2012)
●
Edge-Betweenness (Girvan & Newman, 2001)
●
Fast-Greedy (Clauset et al, 2004)
●
Multi-Level (Blondel et al, 2008)
●
Walktrap (Pons & Latapy, 2005)
●
Infomap (Rosvall, Axelsson & Bergstrom, 2009)
●
17
18. The hyperlink networks we have collected
are both directed and weighted (weight
on edge from node i to j are number of
pages with links from site i to j)
●
Of the above, only Edge-Betweenness
and Infomap support directed and
weighted graphs
●
18
19. Edge-Betweenness
We found the Edge-Betweenness
algorithm (as implemented in igraph/R)
does not scale well.
●
In a test run with UK hyperlink network,
algorithm did not converge after 24 hours
running...
●
19
20. Infomap
See: http://www.mapequation.org
● Scales well for large, dense networks
● information theoretic approach - appropriate to this network,
where there is flow of information and attention
●
If site i links to site j can think of a flow of information from j to i and
a flow of attention from i to j.
● We do not have data on flow of web users from site i to site j i.e.
'clickstream data'
● We therefore make assumption that the number of pages on site i that
contain hyperlinks to site j (these are our edge weights) is proportional
to the flow of attention/information
●
20
21. First attempt...
Tried Infomap implemented in R/iGraph (v. 0.6.5)
● Results: Not good! Algorithm consistently generated a single
massive community (approx. 95% of nodes) and thousands
of tiny communities (1 or 2 nodes per community)
● Results do not pass ‘sanity test’ (i.e. face validity)
● The problem:
●
Many nodes in the UK network have no outlinks
● Therefore, effect of teleportation in the Infomap algorithm is
significant (it randomly connects nodes)
● This problem was solved in Lambiotte and Rosvall (2012)
●
21
22. Second attempt...
Results from Lambiotte and Rosvall (2012) were recently
developed into Infomap algorithm
● This latest code is not yet integrated in R/iGraph
● So, next steps:
●
Download and compile C++ source code for Infomap (v. 0.12.13)
● http://www.mapequation.org/code.html
● Run the standalone Infomap algorithm
●
●
Using Infomap Map Generator, can examine the community
structure of UK network at different scales (varying the number of
communities displayed and number of links between communities)
22
23. 17 out of 4571
communities
(44% of all
flow)
23
24. 45 out of 4571
communities
(70% of all flow)
24
25. Each community is named after the website that has the highest
flow and PageRank in that particular community (i.e. the ‘top
dog’ website)
● Distribution of flow across network follows a power law
●
There are many communities, but a very small percentage ‘hog’ all
the flow across the network
● Top 5% of communities (229 nodes out of 4571) account for about
86% of all flow in the network
●
●
Infomap uses an implementation of the PageRank algorithm to
calculate ‘importance’ of each community (aggregate PageRank
of all websites in that community)
25
26. Preliminary findings
Extremely influential communities form around social media
and blogging platforms
● A massive amount of flow is directed through the ‘Twitter’
community (e.g. from Twitter to www.parliament.uk)
● Many UK seed sites form influential communities (i.e. Top
20), but not all.
● Somewhat unexpectedly, two UK Gov ‘business’ websites
each form highly influential communities
●
http://www.direct.gov.uk (community rank #4, 0.048% of all flow
throughout network)
● http://bis.gov.uk (community rank #8, 0.025% of all flow
throughout network)
●
26
28. ●
To understand the structure of government hyperlink networks, we need to
know something about the websites in these networks
●
●
Generic top-level domains (.edu, .com, org etc.) will only give very coarsegrained information on who these sites are
●
●
What policy domain are they in? (health, education, social security?)
This is social science research so we need more information on nodes
Options:
1. Manually code every site (not feasible, as we have >100K sites)
2. Manually code a subset of sites e.g. the “most important” sites based on
centrality measure (scientifically valid?)
3. Manually code a sample of sites (e.g. adaptive sampling). To be explored in
future...
4. Manually code training dataset and then use machine learning to predict website
type
●
The following is summary of preliminary work on approach 4...
28
29. Data collection
●
Subset of 'important' websites in the UK network were
coded into discrete policy domains by a human coder
Subset chosen as seed sites plus sites connected to two
or more seed sites
● e.g. coding: ‘Community services’, ‘Health’, ‘Foreign
Affairs’
●
Need to collect and ‘clean’ the HTML data from
websites in the network
● While the original VOSON crawl collected text content
for all websites crawled, for this proof of concept, we
re-collected the text content (in future we will use the
VOSON-collected text data)
●
30. Text processing
R ‘XML’ package used to clean the HTML
(strip HTML tags, remove white spaces,
remove strange ASCII characters, convert to
lowercase, extract key word frequencies)
●
2157 websites were usable (i.e. with ‘clean’
web text and a known policy domain)
●
Machine Learning using the ‘RTextTools’
package in R (supervised learning for text
classification)
●
31. Support Vector Machine (SVM)
●
Websites with known policy codes = 2157
SVM ‘training sample’ = 2000
● SVM ‘test sample’ = 157
●
●
Some example results of classification:
PRECISION
RECALL
F-SCORE
Education
0.94
0.83
0.88
Employment
1.00
0.14
0.25
Environment
0.99
0.79
0.88
Foreign Affairs
1.00
0.44
0.61
Health
0.52
0.97
0.68
Housing
0.96
0.79
0.87
32. SVM Conclusion
Surprising level of accuracy
●
Future work will involve:
●
More data (will use HTML collected via
VOSON)
●
Investigate different machine learning
algorithms
●
37. Previous studies
Level
Authors
Result
Small-world effect existed between co-authors and the degree
Newman(2001)
distribution roughly follows the power law in co-authorship networks
in the fields of physics, biomedicine and computer science
Barabasi et al. (2002)
Ramasco et al. (2004)
Co-authorship network in mathematics and neuroscience is scale-free,
and the network evolution is characterized by preferential attachment.
Co-authorships network in the field of condensed matter showed that
the degree distribution follows a power law.
Individual
Co-authorship network in the field of genetic programming changes
Researcher Tomassini and Luthi (2007)
in accordance with preferential attachment
level
International co-authorship grew based on the principle of
Wagner and Leydesdorff
(2005)
preferential attachment, although the attachment mechanism was not
fitted to a pure power law.
Moody (2004)
Brantle and Fallah (2011)
Co-authorship network in sociology does not have a small-world
structure.
Collaboration network of patent inventors has a scale-free power law
property.
4
38. Previous studies
Level
Authors
Result
Verspagen and
Strategic technology alliances, in the two technology fields of chemicals
Duysters (2004)
Powell et al. (2005)
Organization
level
Gay and Dousset (2005)
Barber et al. (2006)
Breschi and Cusmao
(2004)
and food, could be characterized as small worlds.
The alliance network among dedicated biotech firms is scale-free.
The alliance network in the biotechnology industry has a small-world
effect with a scale-free property based on preferential attachment.
Both studies reported the existence of small-world and scale-free
property in inter-organizational R&D relationships from EU-FP
Programmes data.
5
39. Brief history of governmental policy for UIG collaboration (‘00~’11)
6
40. Brief history of governmental policy for UIG collaboration (‘00~’11)
7
42. Methodology
Network topological analysis
Measures
Definition
Density
Average degree
Average path
length
Diameter
The largest geodesic path length in the network
Clustering
coefficient
Degree
centralization
Power law
distribution
9
43. Methodology
Centrality measures
Measures
Degree centrality
Definition
CD(i) = (ΣAi)/(n-1)
* Ai = the number of direct links of node i,
* n = the total number of nodes
Closeness centrality
CC(i) = (n-1)/(ΣDij)
* Dij = the number of links in the geodesic linking node i
and node j
* n = the total number of nodes
Betweenness centrality
CB(i)=[Σj<k gjk(i)/gjk]/[(n-1)(n-2)/2]
* gjk = the number of geodesics linking node j and node k
* gjk(i) = the number of geodesics linking node j and node k
that contain node i
* n = the total number of nodes
10
55. Agenda
1. 3-Helix as a meso-level notion
– Epicycle in a grander tech-psych-inst
cycle
2. Speed (differentials) as high-level
system metric
– Roles of buffering institutions and ICT
– Need for smart engagement
3. Applying 3-helix in the developing
world
4. SUNY Korea’s joint TS/CS research
56. 3-Helix papers published in
Technological Forecasting &
Social Change
• Wilfred Dolfsma, Loet Leydesdorff “Lock-in and break-out from
technological trajectories: Modeling and policy implications,” 76( 7),
Sept. 2009, 932-941.
• Raul Gouvea, Sul Kassicieh, M.J.R. Montoya “Using the quadruple
helix to design strategies for the green economy,” 80(2), Feb. 2013,
221-230.
• Øivind Strand, Loet Leydesdorff “Where is synergy indicated in the
Norwegian innovation system? Triple-Helix relations among
technology, organization, and geography,” 80(3), Mar. 2013, 471-484.
• Inga A. Ivanova, Loet Leydesdorff “Rotational symmetry and the
transformation of innovation systems in a Triple Helix of university–
industry–government relations,” In Press, Corrected Proof, Available
online 19 Sept. 2013.
57. In D.S. Oh & F. Phillips (Eds),
Technopolis: Best Practices for Science
and Technology Cities (Springer, 2014)
• E. Becker, B. Burger and T. Hülsmann,
“Regional Innovation and Cooperation
among Industries, Universities, R&D
Institutes, and Governments”
• F. Phillips, S. Alarakhia and P.
Limprayoon,“The Triple Helix:
International Cases and Critical
Summary”
• José Alberto Sampaio Aranha,
“Arrangement of Actors in the Triple
Helix Innovation”
58. IC2 Model
• Preceded 3-helix by several years
• But only parts were made mathematical (Bard et al)
Ac a d e mi a
Indu st ry
Go v e r n me n t
Com m un it y
Talen t
Technology
Capi t al
Kno w - Ho w
Ma rke t Ne e ds
V alu e - A dd e d
Ec ono m ic Deve lop me nt
59. The math of AcademicGovernment-Industry
dynamics is interesting,
but...
It is just part of a bigger picture.
60. The cycle of innovation and change:
Lab to society & back again
Technological
Innovation
New desires
& dreams
New ways to
organize (Public &
private)
Note how this
schema extends
Everett Rogers’
more linear
model.
New Products
& Services
New ways to
Interact socially
New ways of producing
and using
products & services
61. We might think all the elements
move together in an orderly way.
Social Needs
Institutional Change
Technological Change
Psychological Change
Organizational
Change
62. But in a free-market economy,
they do not.
• They continually
engage and
disengage.
• Sometimes they
move each other
only by friction.
• 90% of MOT and
Tech Policy
problems stem from
the differing speeds
of the 3 sectors.
63. Example: Transportation
• Mobile-web rideshare
services
– Gain VC investment
– Start operations
– Get shut down by city
governments trying to
regulate them under old taxi
rules.
• Institutions have changed
slower than technology
and social demand.
64. Example: Health
• An elderly person dies
because he was too proud
to wear
– A medical bracelet
– or
– An emergency signaller.
• Psychology has changed
slower than technology.
65. Example: Software
• Record companies and publishers
– Sue student MP3 pirates
– Develop DRP software that further alienates
customers
– Can’t adapt away from paper and CD
publishing.
• Business organizations change more
slowly than technology and social
demand.
66. Example: More and more often,
social/institutional change outpaces
tech change - or will do so soon.
• In most of the world, an excess of funds
is chasing too few growth investment
opportunities.
• Fewer US companies are making IPOs.
• Small-government activists rail
indiscriminately against direct
government monetary support for new
technologies.
See Phillips (2011).
67. This can be good.
• Individual creativity
may bloom.
• Mistakes...
– Can be undone
efficiently.
– Don’t necessarily infect
the whole system.
68. It (disengagement)can be bad.
• Alienation
• Lack of coordination and cooperation
• Little institutional or organizational
creativity
• Waste and pollution
• Lives lost
69. Speed as the system metric
• Really, speed
differentials among the
sectors.
• A “clutch” and
“transmission” are
needed.
• The question is less
how to engage, but
rather, when.
• The key is not
engagement per se,
but smart (well-timed)
engagement.
70. Not bridging organizations, but
buffering organizations
•
•
•
•
•
•
•
•
Civic groups
Workforce training programs
Economic development agencies
Technology brokers
Open innovation integrators
Accountancies
Industry associations
NGOs
The IC2 Model partially captured this.
•
•
•
•
Incubators
Law firms
Venture capital
TTOs
71. 3-Helix as meso-level construct: An
epicycle within the TechnologyPsychology-Institutional dynamic
• Macro: Tech-Psych-Inst
• Meso: Aca-Gov-Indus
Tech
– “Triple Helix”
• Micro:
– Dynamics within people and
within organizations;
– Technology life cycles
• The buffering institutions
span all 3 levels.
Inst
(3-Helix)
72. What causes TOPI* disengagement?
*Technological-Organizational-PsychologicalInstitutional
• Bad marketing, bad market research
• Mistrust, bad service
• Technology inaccessible to underserved
populations
• Competition among de facto standards
(e.g., VHS vs Beta)
• Lack of vision
• Poor design of information &
communication products and programs.
75. Marketing guru Geoffrey Moore says,
• “People have disengaged, for ... self-preservation.”
– With “consequences for consumer and brand marketing,
– “and long-term implications for education, health care,
citizen participation, and workforce involvement.
• “So engagement is rightfully going to be a big
investment theme.”
76. Moore: Engagement is taking
center stage in business.
• Off-line retailers are using digital interactions/devices in their
in-store experiences.
– Example: Starbucks.
• “Social marketing foster[s] engagement around topics that ...
reflect well upon the sponsor.”
– Example: Sephora.
• “Big data analytics drive communications that can break
through the wall of detachment.”
– Example: Obama campaign 2012.
77. Moore is saying
• Advertising used to be
like this.
– Annoying! Consumers
disengaged.
• Now with social media,
mobile web, Yelp.com,
– Consumers share product
reviews & complaints.
– Advertisers have to treat
consumers more gently.
– To make us want to
continually re-engage.
• Engaging doesn’t mean
shouting.
81. People are proud to
participate electronically.
• Fighting crime
– Zapruder film; Rodney King videos
• Supporting favorite businesses, authors
– Amazon reviews
• For post-disaster aid
– Crowd-mapping of post-earthquake Haiti
• Crowd-funding research projects and
entrepreneurs
• Though there are abuses.
82. Source: Ganti et al, Mobile
Crowdsensing: Current State and
Future Challenges.
83. Micro Level: Workforce
Engagement
• Definition: The measure of whether
employees merely do the minimum required
of them, versus proactively driving innovation
and new value for the organization.
• Thus, engagement
– “can only ever be partially accounted for by
deploying the latest new collaborative technology,
– “and probably significantly less than many of its
proponents would have you believe.”
Source: Hinchcliffe
86. ICT for engagement? Summary
• ICT alone cannot create/sustain engagement.
– Human intervention, via buffering institutions, can achieve
ICT-aided engagement.
• ICT, especially sensing and crowdsourcing, may
assist in deciding when to engage.
– Thus achieving smart engagement.
• This applies to all 3 levels (macro, meso, micro) of
our multi-level Technology & Society diagram.
87. For many countries where
central government direction is
the norm, 3-helix thinking is
premature.
• Indonesia, Mongolia
• USA: Industry lobbying government
presents a slightly different problem...
89. In sum, the problem is not disengagement, but mis-engagement
among governments, people,
organizations and products, due to:
• Speed differentials (i.e., poor timing)
• Lack of vision
• Poor design of information & communication
products and programs.
– Lack of feedback
– Excess complexity, leading to slow comprehension and
adoption
– Excess technology push (solutions without problems)
– Excess demand pull (unrealistic expectations)
– Other factors
90. SUNY Korea’s research agenda
• Combine social science and computer science...
• To find principles of IT design that more quickly
lead to engagement that is...
– Well-timed
– Smart
– Satisfying
• Among
–
–
–
–
Individuals
Businesses
Government institutions
Technology developers
• With secure applications in several techno-policy
domains (health, energy, etc.).
91. Some Implications
• For IT: Meeting users halfway
• For managers: Engagement plans for
each constituency
• For theorists:
– Modeling the moderating effect of buffering
institutions
– Impact of coalitions on the 3-helix dynamic
92. The math of AcademicGovernment-Industry
dynamics is interesting,
but...
It is just part of a bigger picture.
93. An aside: Spatializing
an innovation
diffusion model
F. Phillips, On S-curves and Tipping Points. Tech.
Forecasting & Social Change, 74(6), July 2007,
715-730.
Alan M. Turing, The chemical basis of morphogenesis. Philosophical Transactions of the
Royal Society of London. B 327, 37–72 (1952)
http://www.cgjennings.ca/toybox/turingmorph/
94. References
• http://davidsasaki.name/2013/01/beyond-technology-fortransparency/
• A. Charnes, S. Littlechild and S. Sorensen, “Core-stem Solutions of
N-person Essential Games.” Socio-Econ. Plan. Sci. Vol. I, pp. 649660 (1973).
• David Watson The Engaged University. Routledge, 2013.
• Dion Hinchcliffe, “Does technology improve employee engagement?”
Enterprise Web 2.0, Nov. 5, 2013. http://www.zdnet.com/doestechnology-improve-employee-engagement-7000021695/
• Jonathan Bard, Boaz Golany and Fred Phillips, “Bubble Planning
and the Mathematics of Consortia.” Third International Conference
on Technology Policy and Innovation, Austin, Texas, September,
1999.
• F. Phillips, The state of technological and social change:
Impressions. Technological Forecasting & SocialChange. 78(6), July
2011, 1072-1078.
96. A Network Analysis of Web-Citations
Among the World’s Universities
George A. Barnett
Department of Communication
University of California, Davis
gbarnett@ucdavis.edu
Daegu Gyeongbuk International Social Network
Conference
December 12-14, 2013
97. Research Aims
• Network Analysis of URL-citations among
– 1,000 universities with greatest presence on WWW (1 million
edges)
– In 58 different countries
– Multi-level analysis (both Universities & Countries)
• Antecedent factors that determine the network’s
structure
– University level
− National Level
• Physical distance
• Same country
Capacity
• Language of instruction
• Size
• Ph.D. granting
• Prestige
• Research Excellence (Nobel Prizes)
Hyperlink Connections
International Bandwidth
GDP, GDP/capita
International Student Flows
Nobel Prizes
98. Data—Web-Citations
• Web-citations among universities collected using Google
– 2,100 X 2,100 matrix of universities (4,407,900 cells) generated
– search query
“university A webdomain” site:university B webdomain
"harvard.edu" site:stanford.edu
− Not all URL-citations are links, e.g., email addresses in coauthored
papers
− Removed universities with no ties & the smaller of a university’s
multiple domains, retained 1,000 most interlinked Universities
− Matrix of inter-citations aggregated to the national level
99. Data--Antecedents
University Level
Physical Location
− Google Maps
Country
− cTLD of website (USA--.edu)
Language of Instruction
− Country of University (India & Singapore—English)
Size of University
− Europe -- (EUMIDA)
(http://thedatahub.org/dataset/eumida)
− U.S. -- College Handbook 2012
− Asia, Africa, Oceania, Latin American & Canada –
Universities’ Websites
Prestige
− U.S. News, World’s Best Universities 2012
http://www.usnews.com/education/
Nobel Prizes
− (http://www.nobelprize.org)
100. Data--Antecedents
National Level
Total Hyperlinks
− Barnett & Park (2012)
International Internet Bandwidth,
GDP & population
− TeleGeography (2012)
(http://www.telegeography.com/)
Student Exchange
− UNESCO (http://stats.uis.unesco.org/unesco)
International Co-authorships
− Leydesdorff & Wagner (2008)
International Citations
− Science Citation Index
101. Results - Universities
•
•
•
•
Over 9.6 million links among 1,000 universities
Density = .606
Mean # of Links = 24.0; S.D. = 2,208.6
Greatest # of links (322,000)
– Universität Trier & Rheinisch Westfalische
Technische Hochschule Aachen, two German
institutions that host huge & popular bibliographic
systems (DBLP & SunSite)
104. Results – Clusters of Universities
Cluster
Defining Attributes
1. German, Swiss & Italian, not English, central, low prestige, less bandwidth
connections
2. English (U.S., Canada, U.K., Australia), central, high prestige, strong bandwidth
connections
3. Low prestige, peripheral, less bandwidth connections
4. English, not French, peripheral, no Ph.D.s, strong bandwidth connections
5. Continental Europe, not English
6. Chinese, less bandwidth connections
7. French, not English, peripheral, lower prestige
8. English, primarily (Jesuit Institutions), peripheral, low prestige
9. English, peripheral
10. Japanese & other Asian, peripheral, little bandwidth connections
105.
106. Results - National
• N = 58 Countries
• Density = .924
• United States most central, followed by Germany, U.K., Canada
– >30% of links ; >4 million outward & 1.9 million inward
– Eigenvector centrality 10 times > Germany
• Gini = .672, a core = periphery structure
– U.S. (359), Germany (67), U.K. (67) & Canada (38) 53.1% of the universities
– These four nations account for 68.3% of the links
– Links distributed by power law; concentrated in a few countries
• Cluster Analysis – 1 group of countries centered about U.S. & U.K.
107.
108. Results – Predicting the Structure of
the University URL-citation Network
• Physical Distance Between Campuses
– QAP Correlation = .005 No relationship between
physical distance and web-citations
• Same Country
–
–
–
–
QAP Correlation = .065
Links 78.4% domestic; 21.6% international
No Links 6.1% domestic; 93.9% international
Mean Link Strength 1,415 with domestic; 42.5
international
• Web-citations tend to be domestic
110. Results – Predicting University
Centrality in Network -- Regression
In-degree
R2
F
P
Size (log)
English
Bandwidth
Rating
Out-Degree
.350
47.94
.000
ß
.279
-.025
.268
.465
Betweenness
.489
85.16
.000
t
6.49
-.516
5.70
10.53
all p< .001, except English for In-degree
ß
.123
.356
.302
.323
t
3.22
8.50
7.31
8.25
Eigenvector
.579
122.25
.000
ß
.282
.185
.336
.502
t
8.13
4.86
8.94
14.12
.310
39.94
.000
ß
.150
.214
.208
.348
t
3.36
4.40
4.33
7.65
111. Results – Predicting the Structure of the
URL-citation Network-National Level
• QAP Correlations with National Level Network
– Co-Authorships .772
– Citations
.967
– Hyperlinks
.545
– Student Flows .270
– Missing Data N = 52 on all except Student Flows,
N = 48
113. Results – Predicting National Centrality
in the Network -- Regression
In-degree
.524
33.78
.000
35.12
.670
ß
R2
F
P
Out-Degree
ß
t
Nobles
English
Population .482 .4.80
GDP/capital .722 7.19
GDP
.000
t
.184 2.27
.398 4.70
.797 9.28
All relations are significant p < .02
Betweenness
22.99
ß
.505
.000
t
.443 4.33
.720 7.03
Eigenvector
.642
31.05
.000
ß t
.553 5.07
.183 2.15
.258 2.41
114. Discussion
• So where is academic knowledge produced?
– Primarily at prestigious English speaking institutions in the U.S.A. &
U.K. , but also in Canada & Germany
• Distance is unrelated to dissemination & collaboration via the
Internet
• Universities tend to link to others from the same country
• Ten clusters- One composed of most prestigious institutions,
suggesting exchanges of knowledge among this group
• Centrality predicted by university size, its prestige (whether it
offered doctoral degrees, its U.S. News ranking, the number of
its faculty’s Noble Prizes), language of instruction (English), &
national international bandwidth capacity
115. Discussion
• At the national level, the countries formed a single group
centered about the U.S. & the U.K.
• U.S. is the most central, followed by Germany, U.K. & Canada
– They accounted for the majority of the universities in the network
• The International Network has a core-periphery structure
with a few countries accounting for the majority of the links
• International co-authorships, citations, student exchanges &
the number of links among the individual countries are
strongly predictive of the network’s structure
• Centrality is predicted, by a country’s population & GDP,
depending on the measure, it may also be predicted by
language of instruction (English) & the number of Noble Prizes
116. Discussion
• Results are consistent with Seeber, et al. (2012)
– European university hyperlink network displays a
center-periphery structure
– centrality a function of the universities’ reputation
– This study extends their conclusions to the global
academic community
117. Discussion
• Consistent with Ortega & Aguilla (2009)
– “The world-class university network graph is comprised of national
sub-networks that merge in a central core where the principal
universities of each country pull their networks toward international
link relationships. This network rests on the United States, which
dominates the world network in conjunction with the aggregation of
the European ones, especially the British and the German subnetworks. This situation may be caused mainly by the technological
development of these countries and the production of international
content, that is, English web pages. This second reason might explain
the apparent backward situation of some East Asian countries.“
• World Systems Theory
– Telephone (Barnett, 2001, 2012)
– Internet (Barnett & Park, 2005, 2012; Park, Barnett & Chung, 2011)
– Student flows (Barnett & Wu, 1995; Chen & Barnett, 2000; Jiang,
2013)
– Patents, trademarks and copyrights (Nam & Barnett, 2011).
118. Discussion
• Global academic community as a self-organizing system
– Academic network may be considered an autopoietic or selfreplicated system
– Evolved from traditional scientific activities (co-authorship,
citing the research of others & other behaviors that required
the sharing of information among scholars)
– Krippendorf defines an autopoietic system as “a network of
processes that produces all the components necessary to
embody the very process that produces it”. The network
recursively produces its components through the interaction
in this historical reproductive network of postings on
university websites & links among institutions
119. Discussion
• There are environmental constraints that limit the
possible states into which this system may evolve
• issues of information property
• policies of individual universities & national governments
• scientific funding agencies (U.S. National Science Foundation)
• Academic networks co-evolved with other global
institutions
• Universally, higher education is developing common
curricula especially in the sciences (Lechner & Boli,
2005). This seems to be reflected in pattern of
universities’ hyperlinks and web-citations
120. Thank you!
See:
Barnett, G.A. , Park, H.W., Jiang, K, Tang, C, & Aguillo, I.F., (2013),
“A multi-level network analysis of web-citations among the
world’s universities”, Scientometrics, DOI 10.1007/s11192-013-1070-0
121. Virtual Knowledge Studio (VKS)
“Webometrics Studies” Revisited
in the Age of “Big Data”
Asso. Prof. Dr. Han Woo PARK
CyberEmotions Research Institute
Dept. of Media & Communication
YeungNam University
214-1 Dae-dong, Gyeongsan-si,
Gyeongsangbuk-do 712-749
Republic of Korea
www.hanpark.net
cerc.yu.ac.kr
eastasia.yu.ac.kr
asia-triplehelix.org
122. Big data
The term “big data” refers to “analytical technologies that
have existed for years but can now be applied faster, on
a greater scale and are accessible to more users. (Miller,
2013).
Big data sizes may vary per discipline.
Characteristics: Garner’s 3Vs plus SAS’s VC and IBM’s
Veracity
- Volume (amount of data), Velocity (speed of data in and
out), Variety (range of data types and sources)
- Variability: Data flows can be highly inconsistent with
daily, seasonal, and event-triggered peak data loads
- Complexity: Multiple data sources requiring cleaning,
linking, and matching the data across system
- Veracity: 1 in 3 business leaders don’t trust the
information they use to make decisions.
http://en.wikipedia.org/wiki/Big_data
http://www-01.ibm.com/software/data/bigdata/
125. Data-driven Research that focuses on
extracting meaningful data from technosocio-economic systems to discover
some hidden patterns.
Today’s “big” is probably tomorrow’s “medium” and
next week’s “small” and thus the most effective definition of “big data” may be derived when the size of data
itself becomes part of the research problem.
Loukides (2012)
126. Introduction
Webometrics is broadly defined as the study of webbased content (e.g., text, images, audio-visual objects, and
hyperlinks) with primarily quantitative indicators for
social science research goals and visualization techniques
derived from information science and social network
analysis.
127. • Han Woo Park
- “hidden” and “relational” data about
lots of people as well as the few
individuals, or small groups
• Lev Manovich
- “surface” data about lots of people (i.e.,
statistical, mathematical or computational
techniques for analyzing data)
- “deep” data about the few individuals or small
groups (i.e., hermeneutics, participant
observation, thick description, semiotics, and
close reading)
7
128. First type of Webometrics
• Hyperlink Network Analysis
- Inter-linkage: who linked to whom matrix
- Co-inlink : a link to two different nodes from a third node
- Co-outlink : A link from two different nodes to a third node
Björneborn (2003)
129. Inter-link network analysis diagram among Korean escience sites within public domain
WCU
WEBOMETRICS
INSTITUTE
Mapping the e-science landscape
In South Korea using the Webometrics method
131. Findings
As seen in Figure 4, the network structure shows a clear butterfly pattern. There is one hub (ghism)
that belongs to Park Gyun-Hye (Park GH, www.cyworld.com/ghism), the daughter of ex-president
Park Jeong-Hee and one of two major GNP candidates (along with president-elect Lee MB) in the
2007 presidential race.
Figure 4: Cyworld Mini-hompies of Korean legislators
How do social scientists use link data
from search engines to understand
Internet-based political and electoral
communication?
WCU
WEBOMETRICS
INSTITUTE
INVESTIGATING INTERNET-BASED POLITICS WITH E-RESEARCH TOOLS
Case 2. Cyworld Mini-hompies of Korean Legislators
132. Sociology of Hyperlink Networks of Web 1.0,
Web 2.0, and Twitter
A Case Study of South Korea
133. Introduction
‣ Online & offline lives ➭ co-constructing (e.g. Beer & Burrows, 2007)
‣ Politicians communicate with their constituencies using different platforms
‣ Questions:
- What are the structural similarities and/or differences in South Korean
politicians’ networks from Web 1.0 to Web 2.0 (and Twitter)?
- Are online structures similar to structures in the physical world?
- Are online patterns affected by offline relationships?
‣ Related studies conducted:
- online social network analysis
- online networks in Web 2.0
- role of Twitter on online politics
134. 2001
2000
‣ 59 isolated in 2000
‣ more centralised in 2001
‣ network of 2001 ➭ a ‘star’ network
- might affected by political events
➭ presidential election in 2001
Web 1.0
135. 2005
2006
‣hubs disappearing
‣easy use of blogs
‣Clear boundaries between different parties
‣strong presence of GNP Assembly members
➭ party policy on using blogs
Web 2.0
138. Bi-linked network of politically active
A-list Korean citizen blogs (July 2005)
URI=Centre
DLP=Left
GNP=Right
Just A-list blogs exchanging links with politicians
139. Affiliation network diagram using pages
linked to Lee’s and Park’s sites
N = 901 (Lee: 215, Park: 692, Shared: 6)
143. “Those studies perpetuate the idea that linking
behaviour is not random, and that links are ‘socially
significant in some way’. In this perspective, links
have an ‘information side-effect’, they can be used
to understand other facts even though they were
not individually designed to do so: ‘information
side-effects are by-products of data intended for
one use which can be mined in order to understand
some tangential, and possibly larger scale,
phenomena’
144. Park and his colleagues were
extensively cited: 9 times!
•
•
•
•
•
•
•
•
•
Barnett GA, Chung CJ and Park HW (2011) Uncovering transnational hyperlink patterns
and web mediated contents: a new approach based on cracking.com domain. Social
Science Computer Review 29(3): 369–384.
Hsu C and Park HW (2011) Sociology of hyperlink networks of Web 1.0, Web 2.0, and
Twitter: a case study of South Korea. Social Science Computer Review 29(3): 354–368.
Park HW (2003) Hyperlink network analysis: a new method for the study of social
structure on the web. Connections 25(1): 49–61.
Park HW (2010) Mapping the e-science landscape in South Korea using the
webometrics method. Journal of Computer-Mediated Communication 15(2): 211–229.
Park HW and Jankowski NW (2008) A hyperlink network analysis of citizen blogs in
South Korean politics. Javnost: The Public 15(2): 5–16.
Park HW and Thelwall M (2003) Hyperlink analyses of the World Wide Web: a review.
Journal of Computer-Mediated Communication 8(4).
Park HW and Thelwall M (2008) Developing network indicators for ideological
landscapes from the political blogosphere in South Korea. Journal of ComputerMediated Communication 13(4): 856–879.
Park HW, Kim C and Barnett GA (2004) Socio-communicational structure among political
actors on the web in South Korea. New Media & Society 6(3): 403–423.
Park HW, Thelwall M and Kluver R (2005) Political hyperlinking in South Korea: technical
indicators of ideology and content. Sociological Research Online 12(3).
145. A comment from those who are
NOT doing a hyperlink analysis
• In a chapter of The Sage Handbook of
Online Research Methods edited by
Fielding et al. (2008), Horgan emphasizes
that ‘link analysis’ has become an active
research domain in examining social
behavior online.
25
146. A threat to Webometrics
• The key application in this area is to collect
some incoming, outgoing, inter-linking, and
co-linking data from search engines
- AltaVista in early 2000
- Yahoo renewed the AltaVista’s hyperlink
commands via “Site Explorer” and its API
- Yahoo discontinued its API option for
interlinkage data in April 2011, and finally
stopped its popular Site Explore service in
November 2011
148. A new proposal
• Mike Thelwall
- URL citation searches with the Bing search
API facilities
• Liwen Vaughan
- Incoming hyperlinks from Alexa.com
Can these "alternative" techniques be
acceptable for scientific publishing?
149. A new proposal : SEO Tools
•
-
Search Engine Optimization Tools
http://www.majesticseo.com/
http://www.opensiteexplorer.org/
https://ahrefs.com/
Enrique Orduña-Malea & John J.
Regazzi (2013). Influence of the academic
Library on U.S. university reputation:
a webometric approach. Technologies. 1,
26-43, http://www.mdpi.com/2227-7080/1/2/26
150. Webometrics Ranking of
World Universities
The link visibility data is collected from the two
most important providers of this
information: Majestic SEO and ahrefs.
Both use their own crawlers, generating different
databases that should be used jointly for filling
gaps or correcting mistakes.
The indicator is the product of square root of the
number of backlinks and the number of
domains originating those backlinks, so it is not
only important the link popularity but even
more the link diversity.
The maximum of the normalized results is the
impact indicator.
http://www.webometrics.info/en/Methodology
151. Interlinkage among world universities
• Barnett, G.A., Park, H. W., Jiang, K., Tang, C.,
& Aguillo, I. F. (2013 forthcoming). A MultiLevel Network Analysis of Web-Citations
Among The World’s Universities.
Scientometrics*.
Isidro F. Aguillo
“Large interlinking matrix (1000*1000) are no
longer possible to obtain. Perhaps national
academic systems (200 or 300 institutions)”
152. Intentional inattention
among Information Scientists?
• Robert Ackland (2013). Web Social Science.
- http://voson.anu.edu.au/
• Richard Rogers (2013). Digital
Methods.
- https://www.issuecrawler.net/index.php
- https://www.digitalmethods.net/Dmi/Tool
Database
153. Let us move to Web Visibility Analysis
Frequently occurring key words in e-science webpages in Korea
Created on Many Eyes(http://many-eyes.com)
Words are larger according to the frequency of their occurrence but their
positions are randomly-chosen for the best visualization
WCU
WEBOMETRICS
INSTITUTE
154. Websites retrieved more than two times
Note: Websites are larger according to their frequency of retrieval; however, heir
colors and locations are randomly-chosen for the best visualization
WCU
WEBOMETRICS
INSTITUTE
155. 2nd type of Webometrics: Web Visibility
Web visibility as an indicator of online political power
Presence or appearance of actors or issues being discussed by
the public (Internet users) on the web.
Tracking web visibility is powerful way to get an insight into
public reactions to actors or issues.
Recent studies indicates the positive relationships
between politicians’ web visibility level and election.
Also, the co-occurrence web visibility between two
politicians represents their hidden online political
relationships based on the public perception.
159. e-리서치 도구의 활용: 웹가시성 분석
블로그 공간에서 후보자들의 웹가시성 수준과 득표 수간
에 밀접한 상관성을 나타냄. (임연수, 박한우, 2010, JKDAS)
실제 득표수
29,120
평균 블로그 수
19,427
14,218
3,071 2,125
504
경대수 정범구 정원헌 박기수 이태희 김경회
161. I. 소셜 미디어의 특징 및 영향력
10.26 재보궐 선거 사례
•
(2)
페이스북에서 이름이 동시에 언급되는 이름 연결망을 구성
하여 분석
•
초반에는 두 후보자가 비슷하게 언급되다가,
중반에 접어들자 박원순 지지자들과 박원순이 언급되면서
나경원 후보자 지지자가 안보이게 되고,
종반에는 박원순 중심으로 네트워크가 재편되며 종결됨
162. I. Semantic network에서 중심성 비교
10.26 재보궐 선거 사례
(2)
•
서울시장 선거 관련 메세지들의 내용
을 분석하여 나오는 단어들의 빈도
분석
•
초반부터 나경원 후보는 빈도가 떨어
지다가, 후반에 박원순 후보와 경쟁
및 선거 결과를 이야기하면서 나타나
는 경우를 제외하고는 줄곳 담론외곽
에 존재
•
안철수 효과는 초반에 크고, 중반이
후 떨이지는 효과가 나타났으나, 한
나라당이라는 언급이 높게 나오면서
집권여당에 반하는 정서가 나타나,
선거의 성격을 말해줌
163.
As Lim & Park (2011, 2013)
claim, the use of web
mentions of politicians’
names is particularly useful
for hierarchically ranking
individual politicians.
However, it may not
sufficiently capture the
entropy probability of an
event (hidden in changing
communication structures)
resulting from the amount of
information conveyed by the
occurrence of that event
(Shannon, 1948).
164.
Taleb (2012) argues that society
can be conceived as a complex
fabric consisting of the extended
disorder family including
uncertainty, chance, entropy, etc.
Therefore, such disorder system
can be better derived from
empirical data mining, not
obtained by a priori theorem.
Uncertainty exists when three or
more events take place
simultaneously and is
increasingly beyond the control of
individual events (Leydesdorff,
2008).
165.
In social and communication
sciences, entropy-based
indicators have been widely
used for exploring entropy
values generated from
university-industrygovernment (UIG)
relationships.
This “Triple Helix Model”
(THM) can be applied to
the concurrence of a pair
of two or three terms in
the public search engine
database
166. Mapping Election Campaigns Through Negative Entropy:
Triple and Quadruple Helix Approach
to Korea’s 2012 Presidential Election
Social media platforms have become a notable venue for Korean
voters wishing to share their opinions and predictions with others
(Park et al., 2011; Sams & Park, 2013).
Politicians have made increasingly use of SNSs to provide updates
and communicate with citizens (Hsu & Park, 2012).
With the increasing proliferation of smartphones and portable
computers in Korea, SNSs have been widely used for facilitating
political discourse.
Prior studies have found that Web 1.0 contents tended to contain the
more enduring political and electoral statements of the public in
various contexts.
167. Introduction
To better understand the dynamics of the 2012 presidential election
in Korea, this study estimates the web visibility of the three major
candidates— Geun-Hye Park (PARK), Cheol-Soo Ahn (AHN), and
Jae-In Moon (MOON)—in the entire digital sphere.
168. Literature Review
The total probabilistic entropy (uncertainty) produced by changes in one or
two dimensions is always positive, which is in accordance with the second
law of thermodynamics (Theil, 1972, p. 59).
On the other hand, the relative contribution of each event to the
summation in three or four dimensions can be positive, zero, or negative
(configurational information).
This configurational information provides a measure of synergy within a
complex communication system. Network effects occur in a systemic and
nonlinear manner when loops in the configuration generate redundancies
in relationships between three or four events (Leydesdorff, 2008).
169. Method: Data collection
The number of hits for each search query per media
channel (Facebook, Twitter, and Google) was harvested.
The hit counts obtained from Google.com were
employed to look primarily at entropies represented on a
set of digitally accessible documents (e.g., online
versions of newspapers, online word-of-mouth, Web 1.0
contents, etc.).
We measured the occurrence and co-occurrence of the
politicians’ names based on their bilateral, trilateral, and
quadruple relationships by using Boolean operators.
For example, we measured the number of web and
social media mentions referring only to PARK (this is, no
mention of AHN, MOON, or the term “president”).
171. Literature Review
Twitter can be very effective to amplify messages particularly in terms of their
one-to-many mode of communication (Barash & Golder, 2010).
Twitter is viable both as a political news and communication channel
(González-Bailón, Borge-Holthoefer, Rivero & Moreno, 2011; Hsu & Park,
2011, 2012; Otterbacher, Shapiro, & Hemphill, 2013)
and to citizens who look for platforms for political participation and engagement
(Hsu, Park, & Park, 2013; Kim & Park, 2011; Tufekci& Wilson, 2012).
172. Literature Review
The mode of information sharing on Facebook differs from that on Twitter.
Facebook functions as a living room where friends talk to one another.
Facebook can be a mixture of interpersonal and mass channels for the sharing of
informational as well as social messages in a context of political campaign (Bond
et al., 2012; Effing, van Hillegersberg, & Huibers, 2011; Robertson, Vatrapu, &
Medina, 2010; Vitak et al., 2011).
Both Twitter and Facebook communications seem to be biased because two
platforms have been particularly dominated by the “2040 Generation”, who are
generally categorized as political liberals in Korea (Kwak et al., 2011).
173. Research questions
Therefore, it is important to examine what (social) media
conversations are more likely to generate more entropies that
others and which politician:
RQ 1) What (social) media generate (negative) entropy more than
others across different periods?
RQ 2) Which politician (or which pair of politicians) generates
entropy more than others for bilateral, trilateral, or quadruple
relationships across various media and periods?
175.
Entropy values (expressed as T for transmission)
for bilateral relationships are, by definition,
positive. Here T is defined as the difference in
uncertainty when the probability distributions of
two incidents (e.g., i and j) are combined. The
mutual information transmission capacity,
expressed in T values, is measured by “bits” of
information (for a more detailed mathematical
definition, see Leydesdorff, 2003):
Hi = – Σi pi log2 (pi); Hij = – Σi Σj pij log2 (pij),
Hij = Hi + Hj – Tij ,
Tij = Hi + Hj – Hij
(1)
Here Tij is zero if the two distributions are mutually
independent and positive otherwise (Theil, 1972).
176.
On the other hand, T values for trilateral and quadruple
relationships can be negative, positive, or zero depending on the
size of contributing terms. Therefore, it is necessary to compare
the absolute value of each (negative) entropy value when entropy
values are calculated for trilateral and quadruple relationships. In
the case of entropy values for trilateral and quadruple
relationships, the higher the absolute entropy value, the more
balanced the communication system is. Let p denote PARK; a,
AHN; and m, MOON and formulate mutual information in these
three dimensions as follows (Abramson. 1963, p. 129):
Tpam = Hp + Ha + Hm – Hpa – Hpm – Ham + Hpam
Here we are interested not only in information on mutual
relationships between these three candidates but also in semantic
relationships with respect to the term “president.” Accordingly, we
measure the entropy value by using mutual information in these
four dimensions (here “r” denotes “president”):
Tpamr = Hp + Ha + Hm + Hr – Hpa – Hpm – Hpr – Ham – Har – Hmr +
Hpam + Hpar + Hpmr + Hamr –Hpamr
(3)
(2)
180. Discussion and conclusions
Twitter has scored the most negative entropy
values and Facebook followed. Google came last.
This indicates that Twitter is the most open
communication system.
The entropy values for liberal candidates (AHN and
MOON) have been higher than their conservative
opponent PARK on social media than Google
sphere.
This may not be surprising because both Twitter
and Facebook have particularly appeared to the
Korean citizens in the age of late teenagers to
early 40s.
181. Discussion and conclusions
PARK’s entropy has been slightly higher on
Google than her liberal challenger MOON.
Park was successful in garnering a strong support
from senior voters in their 50s and 60s accounted
for 39% of the population, up from 29% a decade
ago (Wall Street Journal, 2012).
Exit poll also revealed that PARK gained a support
from 62% of voters in their 50s and 72% of voters
in their 60s. Indeed, the most significant statistic on
the election was that South Koreans in their 20s,
30s, and 40s actually voted 65.2%, 72.5%, and
78.7% respectively but 89.9% in 50s and 78.8%
over 60s went to the polling booth.
182. Paper-code
Keynote Speech
“Creativity and TRIZ”for the Knowledge Network
Analysis in the Emerging Big Data Research”
- DISC 2013 2013. 12. 14.
Dr. Jae Ho Par, Ph.D.
Managing Director of GRCIOP
Professor Emeritus Jae Ho Park
Yeungnam University
183. Curriculum Vitae
Paper-code
December 14, 2013
Professor emeritus Jae H. Park, Ph.D
-
Professor Emeritus , Industrial and Organizational Psychology,
Yeungnam University, South Korea
-Chairman, Global TRIZ Conference, Organizing Committes
- Chairman, Korean Society of Creativity
- Managing Director, GRCIOP Research Center
- Senior Advisor, ICEDR(International Consortium for Executive
Development Research, Boston, USA
- Ph.D., Organizational Psychology, Goettingen University, Germany
- MA, Social Psychology, Seoul National University
- BA, Seoul National University
<Academic Career> -
Harvard University, Research Professor. USA
University of Michigan, Exchange Professor, Ann Arbor, Michigan, USA
Yokohama National University, Research Fellow Professor, Japan
CSPP(California School of Professional Psychology), Teaching Professor, 1999-2000
Senior Advisor, ICEDR(International Consortium for Executive Development Research), USA
Visiting Professor, Meio University, Japan, current
Partner, THT Cross-cultural Consulting, Amsterdam, the Netherlands
Partner, SYMLOG Consulting Group, San Diego, USA
Liscencee, Center for Creative Leadership(CCL), Greensboro, USA,
Partner, Global Integration, UK
184. Paper-code
<International Consulting and Training>
Samsung Electronics; Creativity and Innovation “Change Begins with Me”
Samsung New Management, Train the trainers for 6,000 managers.
JMA(Japan Management Association and FMIC(Future Management and
Innovation Consulting, Japan ), SYMLOG Diagnosis, Team-building and
Coaching, Tokyo, Japan
- LG Philips Displays, M & A Process Consultation, Coaching, Diagnosis
LG Electronics, DAC(White electronics Division), Changwon, Korea
Hyundai Motor Company, Creativity and Innovation Program, Korea
Samsung Electronics, Large Scale Change, Korea
BorgWarner, Detroit, USA
Ericsson, Sweden
Applied Materials Korea, Coaching and Consultation, Seoul, Korea
Goldman Sachs, Integration Project Coaching, with THT Consulting Group, 2007
MetLife, Coaching for Asset Managers, 2007
Mirae Assets Stock Company, Creativity Coaching, 2010
Team-building and Innovation, Trondheim University, Norway
185. Paper-code
<International Network>
Center for Creative Leadership, Partner, Liscencee, North Carolina, USA
SPGR Consulting, Oslo, Norway
JMAC(Japan Management Association Consulting) Tokyo, Japan
SYMLOG Consulting Group, Researcher and Partner, San Diego, USA
Global Integration, Partner, London, United Kingdom
Japan Creativity Research Center, Partner, Tokyo, Japan
THT Cross-cultural Consulting(Trompenaars & Turner), Amsterdam, Partner,
the Netherlands
ICEDR(International Consortium for Executive Development Research) Boston, USA
<Consultant and Advisor >
Samsung HRD
Center
Samsung Electronics
Samsung SDI
LG Education Center
LG Electronics
POSCO HRD Center
<Contact>
Phone; 82-53-810-2230(Office)
Fax; 82-53-810-4610
Mobile; 82-10-8751-7579
email; grciop@gmail.com
186. TRIZ Founder
G. S. Altshuller
(1926~1998)
Father of TRIZ
Global TRIZ Conference 2013 | www.koreatrizcon.kr
Seoul Trade Exhibition & Convention, Seoul, Korea | July 09-11, 2013
187. Paper-code
What is TRIZ ?
TRI Z is a tool for Thinking
but not instead of thinking
G. Altshuller
194. Paper-code
Research
Areas
◦ Understanding creative cognition and
computation
◦ Creativity to stimulate breakthrough in
science and engineering
◦ Educational approaches that encourage
creativity
◦ Supporting creativity with IT
197. Edison and Altshuller
•
•
•
•
•
Everybody can be a Inventor
TRIZ Diffusion; No cost
Developed TRIZ in Prison
Benevolent Mentor
(Dialectics; ideal Communist)
Paper-code
200. Paper-code
Various views on TRIZ
•
•
•
•
•
•
•
From Knowledge Management
From 6 Sigma
From Engineering Design
From Innovation
From Creativity
From R&D
Etc…
202. Paper-code
TRIZ as a Science
Technical
Systems
Social
Systems
Natural
Systems
TRIZ
N&A Narbut, 2003
203. Paper-code
5 Levels of Invention
① Apparent Solution (32%)
①
- Simple
② Simple Improvement within current system
(45%)
③ Major improvement (18%)
- within same science
④ Innovation within current system (4%)
- Application different science principle
⑤ Pioneer Invention (1%)
- New principle and Paradigm Shift
⑤
④
③
②
205. Paper-code
Common Approach
TRIZ
Innovation involves the
creation of new ideas
Innovation involves
adapting existing ideas
Trained in the notion of the
‘great idea’. Popular
mythology - “Einstein” as
model. Belief that ‘six
months in the lab beats one
hour spent in the library’.
Tap existing solutions. Look
outside of discipline and to
Nature. Key benefit:
reduces perceived risk of
innovation (predictable,
higher chance of success).
207. Creativity and TRIZ
Paper-code
*
Korea Academic TRIZ Association
Industry-Academia Knowledge sharing
Contributor for industry competitiveness and
creative talent by TRIZ
Founded in May 2010
Participating of Univ. & Co.
Homepage: www.katatriz.or.kr
32 Co.
29 Univ.
- 3/10 -
208. Paper-code
Main Activities
Expanded use of
TRIZ and social
contribution
Evolution
Nurturing
creative talent
MATRIZ & KATA
MOU
Problem-solving,
Patent-creation
Biz. TRIZ research
Univ. professor
Workshop
Anti-school violence
program
TRIZ education
Charity fair
TRIZ Youth Acamedy
Lectures
for SMEs
Consulting for SMEs
problem-solving
Technical TRIZ
application
2010
2011
2012
2013
Time
- 5/10 -
209. TRIZ Activities in Korea
Paper-code
Company : Development of Innovative Products,
Problem-Solving and Patents Creation
Core tech & innovative product
Foundation of TRIZ Univ.
TRIZ Elite
Development of POSCO methodology
TRIZ research group
Internal TRIZ Conference
Mixing DFSS & TRIZ
Strategic R&D patent creation
Patent creation
On-site TRIZ process designed to
TRIZ research group
improve on-site work performance
- 6/10 -
210. TRIZ Activities in Korea
Paper-code
University : Utilizing TRIZ in subject of “Creative design”
POSTECH
Master course curriculum
TRIZ Project organization
YONSEI
Creative engineering education
Inter-discipline activities and courses
Engineering certification program
HANYANG
Creative design education
Business management and
creative design curriculum
POLYTECHNIC
Mechanical engineering-focused courses
KOREA/RUSSIA cooperation center
※ TRIZ application supported by the government and research institutions
(i.e. Ministry of Trade, Industry and Energy and ETRI)
- 7/10 -
212. Paper-code
Recognition that
(technical) systems evolve
Towards the increase of ideality
By overcoming Contradiction
Mostly with minimal introduction of (free) Resources
Thus, for creative problem solving
TRIZ provides a dialectic ways of thinking, i.e.,
To understand the problem as a system
To image the Ideal solution first
And solve Contradiction
213. Paper-code
GRCIOP Global Network
ICEDR(International Consortium for Executive
Development Research(USA)
Global Integration(United Kingdom)
SYMLOG Consulting Group(USA)
Center for Creative Leadership(USA)
THT Consulting(the Netherlands)
Endre Sjovold Association(Norway)
215. The context
The rise of “new media” has transformed politics,
economics, and societies.
But, “Internet Studies” as a field ignores the
geopolitical issues associated with the rise of new
media technologies
Lots of emphasis on “politics” and the internet, but little on the
relations between states
“Arab Spring”-events occur, but the focus remains primarily on
a domestic context
Likewise, traditional IR theory focuses primarily on
elite level strategy, and doesn’t have the tools to
account for publics
217. Issue 1: The implications of a “networked” globe
on geopolitics
Shifting configurations of influence
Networked, rather than hierarchical
Highly transnational
“foreign” vs “domestic” doesn’t capture the reality
The conversation has become global, especially among
elites
Values
Politics
Economics
But, influence depends on your connectedness to the
global conversation
Thus, dependent on access to technological infrastructure
238. Issue 2: Information Access/Control
Crowd Sourced
Unprecedented access to sensitive information
Stratified
Customized
“The spread of information networks is forming a
new nervous system for our planet. When something
happens in Haiti or Hunan, the rest of us learn about
it in real time-from real people.”
US Sec of StateHillary Clinton, 2010
239. Wikileaks: Crowd-sourced espionage or
invaluable public service?
Revealed US war plans
and operations, as well as
diplomatic secrets
Led to multiple
recriminations, including
attempted assassination
of Saudi ambassador
Snowden: hero or
traitor?
242. Issue Three: Policies
Re-articulation of “national interest”
Alec J. Ross and “21st Century Statecraft”
“addresses new forces propelling change in international
relations that are pervasive, disruptive, and difficult to
predict.” US Dept of State
Perhaps what we can predict
Publics more important than elites
Don’t assume you can keep secrets
Companies comply with national laws more for reputational
reasons than for fear of sanction
243. The Internet Freedom Agenda
“Countries that restrict free access to information or
violate the basic rights of internet users risk walling
themselves off from the progress of the next
century.” Hillary Clinton, January 2010, Remarks
on Internet Freedom
“Let’s be clear. This disclosure is not just an attack
on America-it’s an attack on the international
community.” Hillary Clinton, November 2010, after
the Wikileaks release.
Conclusion: no set of easy answers
244. Final thoughts…..
We need far more sustained attention to the impact
of new media in between states, as well as within
states.
Unrealistic to simply say “NO,” no matter how loudly
we say it. The technology won’t be unmade.
We are in uncharted, and largely unstudied,
territory, and our policies are being driven by what is
technically feasible, rather than what is desirable.
245. A project from the Social Media Research Foundation: http://www.smrfoundation.org
246. About Me
Introductions
Marc A. Smith
Chief Social Scientist
Connected Action Consulting Group
Marc@connectedaction.net
http://www.connectedaction.net
http://www.codeplex.com/nodexl
http://www.twitter.com/marc_smith
http://delicious.com/marc_smith/Paper
http://www.flickr.com/photos/marc_smith
http://www.facebook.com/marc.smith.sociologist
http://www.linkedin.com/in/marcasmith
http://www.slideshare.net/Marc_A_Smith
http://www.smrfoundation.org
248. Social Media Research Foundation
People
Disciplines
Institutions
University
Faculty
Computer Science
University of Maryland
Students
HCI, CSCW
Oxford Internet Institute
Industry
Machine Learning
Stanford University
Independent
Information Visualization
Microsoft Research
Researchers
UI/UX
Illinois Institute of
Technology
Developers
Social Science/Sociology
Connected Action
Network Analysis
Cornell
Collective Action
Morningside Analytics
249. What we are trying to do:
Open Tools, Open Data, Open Scholarship
• Build the “Firefox of GraphML” – open tools for
collecting and visualizing social media data
• Connect users to network analysis – make
network charts as easy as making a pie chart
• Connect researchers to social media data sources
• Archive: Be the “Allen Very Large Telescope Array”
for Social Media data – coordinate and aggregate
the results of many user’s data collection and
analysis
• Create open access research papers & findings
• Make “collections of connections” easy for users
to manage
250. What we have done: Open Tools
• NodeXL
• Data providers (“spigots”)
–
–
–
–
–
–
–
–
ThreadMill Message Board
Exchange Enterprise Email
Voson Hyperlink
SharePoint
Facebook
Twitter
YouTube
Flickr
251. What we have done: Open Data
• NodeXLGraphGallery.org
– User generated collection
of network graphs,
datasets and annotations
– Collective repository for
the research community
– Published collections of
data from a range of social
media data sources to help
students and researchers
connect with data of
interest and relevance
256. There are many kinds of ties….
Send, Mention,
Like, Link, Reply, Rate, Review, Favorite, Friend, Follow, Forward, Edit, Tag, Comment, Check-in…
http://www.flickr.com/photos/stevendepolo/3254238329
257. Social Network Theory
http://en.wikipedia.org/wiki/Social_network
• Central tenet
– Social structure emerges from
– the aggregate of relationships (ties)
– among members of a population
• Phenomena of interest
– Emergence of cliques and clusters
– from patterns of relationships
– Centrality (core), periphery (isolates),
– betweenness
• Methods
– Surveys, interviews, observations,
log file analysis, computational
analysis of matrices
Source: Richards, W.
(1986). The NEGOPY
network analysis
program. Burnaby, BC:
Department of
Communication, Simon
Fraser University. pp.716
(Hampton &Wellman, 1999; Paolillo, 2001; Wellman, 2001)
258. SNA 101
• Node
A
– “actor” on which relationships act; 1-mode versus 2-mode networks
• Edge
B
– Relationship connecting nodes; can be directional
C
• Cohesive Sub-Group
– Well-connected group; clique; cluster
• Key Metrics
A B D E
– Centrality (group or individual measure)
D
• Number of direct connections that individuals have with others in the group (usually look at
incoming connections only)
• Measure at the individual node or group level
E
– Cohesion (group measure)
• Ease with which a network can connect
• Aggregate measure of shortest path between each node pair at network level reflects
average distance
– Density (group measure)
• Robustness of the network
• Number of connections that exist in the group out of 100% possible
G
F
– Betweenness (individual measure)
• # shortest paths between each node pair that a node is on
• Measure at the individual node level
• Node roles
H
I
C
– Peripheral – below average centrality
– Central connector – above average centrality
– Broker – above average betweenness
E
D
259.
260. NodeXL
Free/Open Social Network Analysis add-in for Excel 2007/2010 makes graph
theory as easy as a pie chart, with integrated analysis of social media sources.
http://nodexl.codeplex.com
263. Goal: Make SNA easier
• Existing Social Network Tools are challenging
for many novice users
• Tools like Excel are widely used
• Leveraging a spreadsheet as a host for SNA
lowers barriers to network data analysis and
display
275. Social Network Maps Reveal
Key influencers in any topic.
Sub-groups.
Bridges.
276. NodeXL
Network Overview Discovery and Exploration add-in for Excel 2007/2010
A minimal network can
illustrate the ways different
locations have different values
for centrality and degree
280. Welser, Howard T., Eric Gleave, Danyel Fisher,
and Marc Smith. 2007. Visualizing the Signatures
of Social Roles in Online Discussion Groups.
The Journal of Social Structure. 8(2).
Experts and “Answer People”
Discussion people, Topic setters
Discussion starters, Topic setters
311. SNA questions for social media:
1.
2.
3.
4.
What does my topic network look like?
What does the topic I aspire to be look like?
What is the difference between #1 and #2?
How does my map change as I intervene?
What does #YourHashtag look like?
320. What is Social Network Analysis?
How is it useful for the humanities?
1. New framework for analysis
2. Data visualization allows new perspectives – less linear, more comprehensive
Social Network Analysis and Ancient History
Diane H. Cline, Ph.D.
University of Cincinnati
322. The Content summary
spreadsheet displays the most
frequently used URLs, hashtags,
and user names within the
network as a whole and within
each calculated sub-group.
326. NodeXL as a Teaching Tool
I. Getting Started with Analyzing Social Media Networks
1. Introduction to Social Media and Social Networks
2. Social media: New Technologies of Collaboration
3. Social Network Analysis
II. NodeXL Tutorial: Learning by Doing
4. Layout, Visual Design & Labeling
5. Calculating & Visualizing Network Metrics
6. Preparing Data & Filtering
7. Clustering &Grouping
III Social Media Network Analysis Case Studies
8. Email
9. Threaded Networks
10. Twitter
11. Facebook
12. WWW
13. Flickr
14. YouTube
15. Wiki Networks
http://www.elsevier.com/wps/find/bookdescription.cws_home/723354/description
82
327. What we want to do:
(Build the tools to) map the social web
• Move NodeXL to the web: (Node[NOT]XL)
– Node for Google Doc Spreadsheets?
– WebGL Canvas? D3.JS? Sigma.JS
• Connect to more data sources of interest:
– RDF, MediaWikis, Gmail, NYT, Citation Networks
• Solve hard network manipulation UI problems:
– Modal transform, Time series, Automated layouts
• Grow and maintain archives of social media network data sets for
research use.
• Improve network science education:
– Workshops on social media network analysis
– Live lectures and presentations
– Videos and training materials
328. NodeXL Results
• Easy to learn, yet powerful and insightful
• Widely used by both students and researchers
• Free and open source sofware
• World-wide team of collaborators
Malik S, Smith A, Papadatos P, Li J, Dunne C, and Shneiderman B (2013), “TopicFlow: Visualizing topic
alignment of Twitter data over time. In ASONAM '13.
Bonsignore EM, Dunne C, Rotman D, Smith M, Capone T, Hansen DL and Shneiderman B (2009), "First steps
to NetViz Nirvana: Evaluating social network analysis with NodeXL", In CSE '09. pp. 332-339.
DOI:10.1109/CSE.2009.120
Mohammad S, Dunne C and Dorr B (2009), "Generating high-coverage semantic orientation lexicons from
overtly marked words and a thesaurus", In EMNLP '09. pp. 599-608.
Smith M, Shneiderman B, Milic-Frayling N, Rodrigues EM, Barash V, Dunne C, Capone T, Perer A and Gleave E
(2009), "Analyzing (social media) networks with NodeXL", In C&T '09. pp. 255-264.
84
DOI:0.1145/1556460.1556497
329. How you can help
Sponsor a feature
Sponsor workshops
Sponsor a student
Schedule training
Sponsor the foundation
Donate your money, code, computation, storage,
bandwidth, data or employee’s time
• Help promote the work of the Social Media
Research Foundation
•
•
•
•
•
•
332. A project from the Social Media Research Foundation: http://www.smrfoundation.org
333.
334. International Collaboration &
Green Technology Generation
Assessing the East Asian
Environmental Regime
Matthew A. Shapiro
Illinois Institute of Technology
matthew.shapiro@iit.edu
335. Impetus
• Shapiro and Nugent (2012) “Institutions and the
sources of innovation” in IJPP
• Total factor productivity is hindered by collaboration if
institutions are absent or if not beyond TFP threshold
• Shapiro (2013) “Regionalism’s challenge to the
pollution haven hypothesis” in Pacific Review
• Regional efforts to eliminate pollution are
multifaceted
• Support
• East Asia Institute
• Asiatic Research Institute, Korea University
336. International
institutions
To other regions
To other regions
Regional institutions
Country 2 FDI
Country 2
ecologists
(+)
Pollution
haven
hypothesis
(+)
(+)
Epistemic
community
hypothesis
(-)
Country 1
pollution
Country 2
pollution
Country 3
pollution
Country 1
institutions
(-)
Country 2
domestic R&D
funding
Country 3
domestic R&D
funding
Country 3
ecologists
Country 3 FDI
Contra-pollution
haven
hypothesis (-)
Country 1
domestic R&D
funding
Country 1
ecologists
Country 1 FDI
Country 2
institutions
Country 3
institutions
337.
338. International
institutions
To other regions
To other regions
Regional institutions
Country 2 FDI
Country 2
ecologists
(+)
Pollution
haven
hypothesis
(+)
(+)
Epistemic
community
hypothesis
(-)
Country 1
pollution
Country 2
pollution
Country 3
pollution
Country 1
institutions
(-)
Country 2
domestic R&D
funding
Country 3
domestic R&D
funding
Country 3
ecologists
Country 3 FDI
Contra-pollution
haven
hypothesis (-)
Country 1
domestic R&D
funding
Country 1
ecologists
Country 1 FDI
Country 2
institutions
Country 3
institutions
339.
340. International
institutions
To other regions
To other regions
Regional institutions
Country 2 FDI
Country 2
ecologists
(+)
Pollution
haven
hypothesis
(+)
(+)
Epistemic
community
hypothesis
(-)
Country 1
pollution
Country 2
pollution
Country 3
pollution
Country 1
institutions
(-)
Country 2
domestic R&D
funding
Country 3
domestic R&D
funding
Country 3
ecologists
Country 3 FDI
Contra-pollution
haven
hypothesis (-)
Country 1
domestic R&D
funding
Country 1
ecologists
Country 1 FDI
Country 2
institutions
Country 3
institutions
341.
342. Research Questions
• Are the Northeast Asian countries key
collaborators in pursuit of green R&D?
• Yes, particularly in recent years.
• Are the Northeast Asian countries
collaborating extensively with each other?
• Not as much as they collaborate with countries
beyond the region.
• Implications?
343. Green R&D
• Patents
• IPC Green Inventory
•
•
•
•
•
•
•
Alternative energy production
Transportation
Energy conservation
Waste management
Agriculture/forestry
Administrative aspects
Nuclear power generation
344. Alternative energy production
• Biofuels
• Integrate gasification combined cycle
• Fuel cells
• Pyrolysis or gasification of biomass
• Harnessing energy from manmade
waste
• Hydro energy
• Ocean thermal energy conversion
• Wind energy
• Solar energy
• Geothermal energy
• Other production or use of heat not
derived from combustion
• Using waste heat
• Devices for producing mechanical
power from muscle energy
Energy conservation
• Storage of electrical
energy
• Power supply
circuitry
• Measurement of
electricity
consumption
• Storage of thermal
energy
• Low energy lighting
• Thermal building
insulation, in general
• Recovering
mechanical energy
345. Data Collection
• Source: USPTO
• Collection method: Leydesorff’s tools
• Unit of analysis: country of inventor
346. Data Description
IL
BE
• Dates: 1990-2013
• 129,640 total inventors
IN
IT
CN
CH
NZ TW
all others
AU
KR
DK
• Assumption: Any
collaboration is valued,
so proportionate share
of patent inventorship is
ignored.
CA
GB
• 242,331 total nodes
based on country
classification
NL
FR
US
DE
JP
361. Implications
• Empirical
• R&D collaboration can be beneficial from both
intra- as well as extra-regionally. Both are
happening extensively for Northeast Asia.
• Methodological
• Challenges of connecting these results to other
variables in model
• Longitudinal concerns: Change in connectedness?
• Qualitative, quantitative, mixed?
362. Assessing Social Media Coverage in
Japan: Before and After March 11, 2011
Leslie M. Tkach-Kawasaki
University of Tsukuba
DISC 2013, December 11, 2013
365. Social Media in Japan 2010-2011
Have used the following at least once…..
Blogs 77.3%
Video-sharing websites 62.8%
SNS 53.6%
Microblogs (Twitter) 30.9%
Source: 2010 White Paper on Information and Communications in Japan
366. The Year in Social Media 2010-11
International diplomacy:Youtube and Chinese
fishing vessel (September 2010)
Entertainment: Release of The Social Network
(October 2010)
International conflicts: Role of Twitter and
Facebook in Tunisia and Egypt (January 2011)
Disasters: New Zealand Earthquake (February
2011)
369. Research question….
Are there perceivable differences
in the discourse (phrases) about
social media in Japan’s
newspaper media before and after
March 11, 2011?