The Evidence Hub: Harnessing the Collective Intelligence of Communities to Bu...Anna De Liddo
Presentation to the Large-Scale Idea Management and Deliberation Systems Workshop @
6th International Conference on Communities and Technologies C&T2013
June 29,2013
Munich, Germany
Collective Intelligence and Online Deliberation Platforms for Citizen Engagem...Anna De Liddo
This is the presentation of the keynote I gave to the The "Software Codes of Democracy: Web Platforms for New Politics Workshop, which was held in Milan, Italy 13-15 Sept 2013 http://codicidellademocrazia.partecipate.it/
Abstract
Social media are increasingly used to support online debate and facilitate citizens’ engagement in policy and decision-making. Nevertheless the online dialogue spaces we see on the Web today typically provide flat listings of comments, or threads that can be viewed by ‘subject’ line. These are fundamentally chronological views which offer no insight into the logical structure of the ideas, such as the coherence or evidential basis of an argument. This hampers both quality of citizens’ participation and effective assessment of the state of the debate.
Within the landscape of existing community debate and ideation tools, the talk will introduce a new class of emerging online deliberation platforms – coming from research on Hypermedia, Collective Intelligence and Argumentation – that enable more structured, engaging and transparent online deliberation processes.
The talk will focus on the description of some of these technologies and summarise research studies in which they have been used to effectively support online deliberation in the Education, Healthcare and Public sector.
The talk will conclude proposing reflections and future research on collective intelligence and online deliberation platforms to socially innovate and to re-engage citizens with the democratic process.
Divoli Presentation at EBI Apr2011 Usability PartAnna Divoli
Part of a talk given by Anna Divoli at EBI in April 2011.
Outline of three usability studies conducted for the development of the BioText Search Engine.
http://biosearch.berkeley.edu/
The Innovation Engine for Team Building – The EU Aristotele Approach From Ope...ARISTOTELE
ARISTOTELE approach has been presented at the Innovation Adoption Forum for Industry and Public Sector within the 6th IEEE International Conference on Digital Ecosystem Technologies (IEEE DEST - CEE 2012). The presentation about ARISTOTELE has been held by Paolo Ceravolo and Ernesto Damiani (University of Milan) during the keynote "The Innovation Engine for Team Building – The EU Aristotele Approach". Learn more on http://www.aristotele-ip.eu/
The Evidence Hub: Harnessing the Collective Intelligence of Communities to Bu...Anna De Liddo
Presentation to the Large-Scale Idea Management and Deliberation Systems Workshop @
6th International Conference on Communities and Technologies C&T2013
June 29,2013
Munich, Germany
Collective Intelligence and Online Deliberation Platforms for Citizen Engagem...Anna De Liddo
This is the presentation of the keynote I gave to the The "Software Codes of Democracy: Web Platforms for New Politics Workshop, which was held in Milan, Italy 13-15 Sept 2013 http://codicidellademocrazia.partecipate.it/
Abstract
Social media are increasingly used to support online debate and facilitate citizens’ engagement in policy and decision-making. Nevertheless the online dialogue spaces we see on the Web today typically provide flat listings of comments, or threads that can be viewed by ‘subject’ line. These are fundamentally chronological views which offer no insight into the logical structure of the ideas, such as the coherence or evidential basis of an argument. This hampers both quality of citizens’ participation and effective assessment of the state of the debate.
Within the landscape of existing community debate and ideation tools, the talk will introduce a new class of emerging online deliberation platforms – coming from research on Hypermedia, Collective Intelligence and Argumentation – that enable more structured, engaging and transparent online deliberation processes.
The talk will focus on the description of some of these technologies and summarise research studies in which they have been used to effectively support online deliberation in the Education, Healthcare and Public sector.
The talk will conclude proposing reflections and future research on collective intelligence and online deliberation platforms to socially innovate and to re-engage citizens with the democratic process.
Divoli Presentation at EBI Apr2011 Usability PartAnna Divoli
Part of a talk given by Anna Divoli at EBI in April 2011.
Outline of three usability studies conducted for the development of the BioText Search Engine.
http://biosearch.berkeley.edu/
The Innovation Engine for Team Building – The EU Aristotele Approach From Ope...ARISTOTELE
ARISTOTELE approach has been presented at the Innovation Adoption Forum for Industry and Public Sector within the 6th IEEE International Conference on Digital Ecosystem Technologies (IEEE DEST - CEE 2012). The presentation about ARISTOTELE has been held by Paolo Ceravolo and Ernesto Damiani (University of Milan) during the keynote "The Innovation Engine for Team Building – The EU Aristotele Approach". Learn more on http://www.aristotele-ip.eu/
Social and Collaborative Construction of Structured Knowledge WWW2007Simon Buckingham Shum
Sereno, B., Buckingham Shum, S. and Motta, E. (2007). Formalization, User Strategy and Interaction Design: Users’ Behaviour with Discourse Tagging Semantics. Workshop on Social and Collaborative Construction of Structured Knowledge, 16th International World Wide Web Conference (WWW 2007), Banff, AB, Canada; 8-12 May 2007. [http://www2007.org/workshops/paper_30.pdf]
Hidden Gems in the Wikipedia discussions: The Wikipedians' RationalesLu Xiao
This is a presentation I gave at 2019 Wikimania Research in Sweden (August 17). It gives an overview of our research projects related to Wikipedia's Article for Deletion (AfD) discussions, with a focus on the rationales in the discussions
Invited talk at Session on Semantic Knowledge for Commodity Computing, at Microsoft Research Faculty Summit 2011, July 19-20, 2011, Redmond, WA. http://research.microsoft.com/en-us/events/fs2011/default.aspx
Associated video at: https://youtu.be/HKqpuLiMXRs
Understanding everyday users’ perception of socio-technical issues through s...Ahreum lee
I gave a talk at ImagineXLab, Seoul, Korea.
In this presentation, I would like to share my recent works that have been explored sociotechnical issues through social media data.
1) /r/Assholedesign: Online conversation about ethical concerns (ACM DIS 20' Honorable Mention Award)
2) /r/Digitalnomad: Current tensions in community-based spaces (ACM CHI 2019 LBW, CSCW 2019)
3) /r/Purdue: Everyday users’ perception of delivery robots on campus (ACM CSCW 2020 LBW)
Building and Communicating Evidence of Effectiveness in OER through Collectiv...Robert Farrow
Much of the evidence surrounding the use (and re-use) of OER is fragmentary or anecdotal. The OLnet project has developed a software tool for effectively gathering, sharing and judging the evidence around key issues of OER. The Evidence Hub distills key insights from the cloud of discussion and opinion creating a thematically indexed, structured ecosystem of organisations, project, issues, recommendations and evidence for the use of those who form the Open Education movement. In this presentation we explain the key concepts behind the Evidence Hub and some of its possible uses.
Designing for Collaboration: Challenges & Considerations of Multi-Use Informa...Stephanie Steinhardt
Slides assembled for Human Centered Design & Engineering Preliminary Exam talk at the University of Washington Allen Library Auditorium 4.8.2011.
Thanks to Mark Zachry, David McDonald, Elly Searle, Carol Allen, and NSF IIS-0811210.
Tracking Social Media Participation: New Approaches to Studying User-Gener...Axel Bruns
PhD Seminar
Thursday 29 Oct., 9.30-11 a.m.
Seminar Room, Journalism & Media Research Centre, 1-3 Eurimbla St (corner High St), Randwick
The impact of user-generated content on a variety of media industries and practices is by now well understood from a conceptual perspective (e.g. Benkler 2006; Jenkins 2006; Bruns 2008). What remains less thoroughly explored is the possibility to utilise the affordances of Web 2.0 technologies themselves to generate large datasets that can be used to track and evaluate user participation practices in order to develop a solid evidence base for further research into social media, and further development of social media projects, technologies, and policies. This presentation outlines research possibilities across a number of social media spaces, and uses the example of a current research project studying the Australian political blogosphere to explore potential methodological approaches.
Presentation about our community-driven approach for reputation eliciting and estimation, given at the Altmetrics Workshop, during WebSci Conference 2011 held in Koblenz, Germany.
H. Purohit, Y. Ruan, A. Joshi, S. Parthasarathy, A. Sheth. Understanding User-Community Engagement by Multi-faceted Features: A Case Study on Twitter. in SoME 2011 (Workshop on Social Media Engagement, in conjunction with WWW 2011), March 29, 2011.
Paper: http://knoesis.org/library/resource.php?id=1095
More on Social Media @ Kno.e.sis at http://knoesis.org/research/semweb/projects/socialmedia/
Changing trends in citation analysis and challenges in API measurementMunesh Kumar
Changing trends in citation analysis and challenges in API measurement article focused on the changing theme of citation analysis and evaluation of Altmetrics, and issues in academic performance Indicator (API).
analyze, and discuss emerging ICT tools and technologies present.docxjack60216
analyze, and discuss emerging ICT tools and technologies presenting the potential to enhance policy making. Visualization tool are discussed in
Visualization tools help users better understand data and provide a more meaningful view in context, especially by presenting data in a graphical form.
Produce a definition of data visualization. Explain how it caters to the perceptual abilities of humans.
Describe three challenges data visualization researchers face when trying to use visualization tools to reinforce the policy-making process. Suggest solutions to conquer these three challenges.
Initial Post:
Create a new thread. As indicated above, (1) Produce a definition of data visualization. Explain how it caters to the perceptual abilities of humans. (2) Describe three challenges data visualization researchers face when trying to use visualization tools to reinforce the policy-making process. Suggest solutions to conquer these three challenges.
In order to receive full credit for the initial discussion post, you must include at least two citations (APA) from academic resources
.
Stepping out of the echo chamber - Alternative indicators of scholarly commun...Andy Tattersall
This set of slides which was presented at Sheffield Hallam University and The London School of Hygene and Tropical Medicine. They showcase the many ways academics can leverage digital scholary communication tools to discover what is being said about their research and how best to respond to that conversation.
Open Science Framework (OSF): Presentation and TrainingAndrew Sallans
Presentation Date: December 12, 2013.
Location: UC Berkeley, CA
Presenters: Johanna Cohoon & Andrew Sallans (Center for Open Science)
Center for Open Science website: http://centerforopenscience.org
Berkeley Initiative for Transparency in the Social Sciences website: http://bitss.org/annual-meeting/2013-2/
2017 10-10 (netflix ml platform meetup) learning item and user representation...Ed Chi
Learning item and user representations with sparse data in recommender systems
Ed H. Chi
Google Inc.
Recommenders match users in a particular context with the best personalized items that they will engage with. The problem is that users have shifting item and topic preferences, and give sparse feedback over time (or no-feedback at all). Contexts shift from interaction-to-interaction at various time scales (seconds to minutes to days). Learning about users and items is hard because of noisy and sparse labels, and the user/item set changes rapidly and is large and long-tailed. Given the enormity of the problem, it is a wonder that we learn anything at all about our items and users.
In this talk, I will outline some research at Google to tackle the sparsity problem. First, I will summarize some work on focused learning, which suggests that learning about subsets of the data requires tuning the parameters for estimating the missing unobserved entries. Second, we utilize joint feature factorization to impute possible user affinity to freshly-uploaded items, and employ hashing-based techniques to perform extremely fast similarity scoring on a large item catalog, while controlling variance. This approach is currently serving a ~1TB model on production traffic using distributed TensorFlow Serving, demonstrating that our techniques work in practice. I will conclude with some remarks on possible future directions.
HCI Korea 2012 Keynote Talk on Model-Driven Research in Social ComputingEd Chi
Model-Driven Research in Social Computing
Research in Augmented Social Cognition is aimed at enhancing the ability of a group of people to remember, think, and reason. Our approach to creating this augmentation or enhancement is primarily model-driven. Our system developments are informed by models such as information scent, sensemaking, information theory, probabilistic models, and more recently, evolutionary dynamic models. These models have been used to understand a wide variety of user behaviors, from individuals interacting with social bookmark search in Delicious and MrTaggy.com to groups of people working on articles in Wikipedia. These models range in complexity from a simple set of assumptions to complex equations describing human and group behaviors.
By studying online social systems such as Google Plus, Twitter, Delicious, and Wikipedia, we further our understanding of how knowledge is constructed in a social context. In this talk, I will illustrate how a model-driven approach could help illuminate the path forward for research in social computing and community knowledge building.
More Related Content
Similar to China HCI Symposium 2010 March: Augmented Social Cognition Research from PARC, by Ed H. Chi
Social and Collaborative Construction of Structured Knowledge WWW2007Simon Buckingham Shum
Sereno, B., Buckingham Shum, S. and Motta, E. (2007). Formalization, User Strategy and Interaction Design: Users’ Behaviour with Discourse Tagging Semantics. Workshop on Social and Collaborative Construction of Structured Knowledge, 16th International World Wide Web Conference (WWW 2007), Banff, AB, Canada; 8-12 May 2007. [http://www2007.org/workshops/paper_30.pdf]
Hidden Gems in the Wikipedia discussions: The Wikipedians' RationalesLu Xiao
This is a presentation I gave at 2019 Wikimania Research in Sweden (August 17). It gives an overview of our research projects related to Wikipedia's Article for Deletion (AfD) discussions, with a focus on the rationales in the discussions
Invited talk at Session on Semantic Knowledge for Commodity Computing, at Microsoft Research Faculty Summit 2011, July 19-20, 2011, Redmond, WA. http://research.microsoft.com/en-us/events/fs2011/default.aspx
Associated video at: https://youtu.be/HKqpuLiMXRs
Understanding everyday users’ perception of socio-technical issues through s...Ahreum lee
I gave a talk at ImagineXLab, Seoul, Korea.
In this presentation, I would like to share my recent works that have been explored sociotechnical issues through social media data.
1) /r/Assholedesign: Online conversation about ethical concerns (ACM DIS 20' Honorable Mention Award)
2) /r/Digitalnomad: Current tensions in community-based spaces (ACM CHI 2019 LBW, CSCW 2019)
3) /r/Purdue: Everyday users’ perception of delivery robots on campus (ACM CSCW 2020 LBW)
Building and Communicating Evidence of Effectiveness in OER through Collectiv...Robert Farrow
Much of the evidence surrounding the use (and re-use) of OER is fragmentary or anecdotal. The OLnet project has developed a software tool for effectively gathering, sharing and judging the evidence around key issues of OER. The Evidence Hub distills key insights from the cloud of discussion and opinion creating a thematically indexed, structured ecosystem of organisations, project, issues, recommendations and evidence for the use of those who form the Open Education movement. In this presentation we explain the key concepts behind the Evidence Hub and some of its possible uses.
Designing for Collaboration: Challenges & Considerations of Multi-Use Informa...Stephanie Steinhardt
Slides assembled for Human Centered Design & Engineering Preliminary Exam talk at the University of Washington Allen Library Auditorium 4.8.2011.
Thanks to Mark Zachry, David McDonald, Elly Searle, Carol Allen, and NSF IIS-0811210.
Tracking Social Media Participation: New Approaches to Studying User-Gener...Axel Bruns
PhD Seminar
Thursday 29 Oct., 9.30-11 a.m.
Seminar Room, Journalism & Media Research Centre, 1-3 Eurimbla St (corner High St), Randwick
The impact of user-generated content on a variety of media industries and practices is by now well understood from a conceptual perspective (e.g. Benkler 2006; Jenkins 2006; Bruns 2008). What remains less thoroughly explored is the possibility to utilise the affordances of Web 2.0 technologies themselves to generate large datasets that can be used to track and evaluate user participation practices in order to develop a solid evidence base for further research into social media, and further development of social media projects, technologies, and policies. This presentation outlines research possibilities across a number of social media spaces, and uses the example of a current research project studying the Australian political blogosphere to explore potential methodological approaches.
Presentation about our community-driven approach for reputation eliciting and estimation, given at the Altmetrics Workshop, during WebSci Conference 2011 held in Koblenz, Germany.
H. Purohit, Y. Ruan, A. Joshi, S. Parthasarathy, A. Sheth. Understanding User-Community Engagement by Multi-faceted Features: A Case Study on Twitter. in SoME 2011 (Workshop on Social Media Engagement, in conjunction with WWW 2011), March 29, 2011.
Paper: http://knoesis.org/library/resource.php?id=1095
More on Social Media @ Kno.e.sis at http://knoesis.org/research/semweb/projects/socialmedia/
Changing trends in citation analysis and challenges in API measurementMunesh Kumar
Changing trends in citation analysis and challenges in API measurement article focused on the changing theme of citation analysis and evaluation of Altmetrics, and issues in academic performance Indicator (API).
analyze, and discuss emerging ICT tools and technologies present.docxjack60216
analyze, and discuss emerging ICT tools and technologies presenting the potential to enhance policy making. Visualization tool are discussed in
Visualization tools help users better understand data and provide a more meaningful view in context, especially by presenting data in a graphical form.
Produce a definition of data visualization. Explain how it caters to the perceptual abilities of humans.
Describe three challenges data visualization researchers face when trying to use visualization tools to reinforce the policy-making process. Suggest solutions to conquer these three challenges.
Initial Post:
Create a new thread. As indicated above, (1) Produce a definition of data visualization. Explain how it caters to the perceptual abilities of humans. (2) Describe three challenges data visualization researchers face when trying to use visualization tools to reinforce the policy-making process. Suggest solutions to conquer these three challenges.
In order to receive full credit for the initial discussion post, you must include at least two citations (APA) from academic resources
.
Stepping out of the echo chamber - Alternative indicators of scholarly commun...Andy Tattersall
This set of slides which was presented at Sheffield Hallam University and The London School of Hygene and Tropical Medicine. They showcase the many ways academics can leverage digital scholary communication tools to discover what is being said about their research and how best to respond to that conversation.
Open Science Framework (OSF): Presentation and TrainingAndrew Sallans
Presentation Date: December 12, 2013.
Location: UC Berkeley, CA
Presenters: Johanna Cohoon & Andrew Sallans (Center for Open Science)
Center for Open Science website: http://centerforopenscience.org
Berkeley Initiative for Transparency in the Social Sciences website: http://bitss.org/annual-meeting/2013-2/
2017 10-10 (netflix ml platform meetup) learning item and user representation...Ed Chi
Learning item and user representations with sparse data in recommender systems
Ed H. Chi
Google Inc.
Recommenders match users in a particular context with the best personalized items that they will engage with. The problem is that users have shifting item and topic preferences, and give sparse feedback over time (or no-feedback at all). Contexts shift from interaction-to-interaction at various time scales (seconds to minutes to days). Learning about users and items is hard because of noisy and sparse labels, and the user/item set changes rapidly and is large and long-tailed. Given the enormity of the problem, it is a wonder that we learn anything at all about our items and users.
In this talk, I will outline some research at Google to tackle the sparsity problem. First, I will summarize some work on focused learning, which suggests that learning about subsets of the data requires tuning the parameters for estimating the missing unobserved entries. Second, we utilize joint feature factorization to impute possible user affinity to freshly-uploaded items, and employ hashing-based techniques to perform extremely fast similarity scoring on a large item catalog, while controlling variance. This approach is currently serving a ~1TB model on production traffic using distributed TensorFlow Serving, demonstrating that our techniques work in practice. I will conclude with some remarks on possible future directions.
HCI Korea 2012 Keynote Talk on Model-Driven Research in Social ComputingEd Chi
Model-Driven Research in Social Computing
Research in Augmented Social Cognition is aimed at enhancing the ability of a group of people to remember, think, and reason. Our approach to creating this augmentation or enhancement is primarily model-driven. Our system developments are informed by models such as information scent, sensemaking, information theory, probabilistic models, and more recently, evolutionary dynamic models. These models have been used to understand a wide variety of user behaviors, from individuals interacting with social bookmark search in Delicious and MrTaggy.com to groups of people working on articles in Wikipedia. These models range in complexity from a simple set of assumptions to complex equations describing human and group behaviors.
By studying online social systems such as Google Plus, Twitter, Delicious, and Wikipedia, we further our understanding of how knowledge is constructed in a social context. In this talk, I will illustrate how a model-driven approach could help illuminate the path forward for research in social computing and community knowledge building.
Location and Language in Social Media (Stanford Mobi Social Invited Talk)Ed Chi
http://forum.stanford.edu/events/2012mobi.php
Title: Location and Language in Social Media
Ed H. Chi
Staff Research Scientist, Google Research
(work done at [Xerox] PARC)
Abstract:
Despite the widespread adoption of social media internationally,
little research has investigated the differences among users of
different languages. Moreover, we know relatively little about how
people reveal their location information. In this talk, I will
outline our recent characterization studies on how users of differing
geographical locations and languages use social media.
First, on geographical location: We found that 34% of users did not
provide real location information in Twitter, frequently incorporating
fake locations or sarcastic comments that can fool traditional
geographic information tools. We performed a simple machine learning
experiment to determine whether we can identify a user’s location by
only looking at what that user tweets.
Second, on language, Examining users of the top 10 languages, we
discovered cross-language differences in adoption of features such as
URLs, hashtags, mentions, replies, and retweets.
We discuss our work’s implications for research on large-scale social
systems and design of cross-cultural communication tools.
Homepage:
edchi.net
Speaker Bio:
Ed H. Chi is a Staff Research Scientist at Google. Until recently, he
was the Area Manager and a Principal Scientist at Palo Alto Research
Center's Augmented Social Cognition Group. He led the group in
understanding how Web2.0 and Social Computing systems help groups of
people to remember, think and reason. Ed completed his three degrees
(B.S., M.S., and Ph.D.) in 6.5 years from University of Minnesota, and
has been doing research on user interface software systems since 1993.
He has been featured and quoted in the press, including the Economist,
Time Magazine, LA Times, and the Associated Press.
With 20 patents and over 90 research articles, his most well-known
past project is the study of Information Scent --- understanding how
users navigate and understand the Web and information environments. He
also led a group of researchers at PARC to understand the underlying
mechanisms in online social systems such as Wikipedia and social
tagging sites. He has also worked on information visualization,
computational molecular biology, ubicomp, and recommendation/search
engines, and has won awards for both teaching and research. In his spare time, Ed is an avid Taekwondo martial artist, photographer, and
snowboarder.
Model-Driven Research in Social Computing
Abstract:
Research in Augmented Social Cognition is aimed at enhancing the ability of a group of people to remember, think, and reason. Our approach to creating this augmentation or enhancement is primarily model-driven. Our system developments are informed by models such as information scent, sensemaking, information theory, probabilistic models, and more recently, evolutionary dynamic models. These models have been used to understand a wide variety of user behaviors, from individuals interacting with social bookmark search in Delicious and MrTaggy.com to groups of people working on articles in Wikipedia. These models range in complexity from a simple set of assumptions to complex equations describing human and group behaviors.
By studying online social systems such as Google Plus, Twitter, Delicious, and Wikipedia, we further our understanding of how knowledge is constructed in a social context. In this talk, I will illustrate how a model-driven approach could help illuminate the path forward for research in social computing and community knowledge building
Bio: Ed H. Chi is a Staff Research Scientist at Google, working on the Google+ project. Very recently, Ed was the Area Manager and a Principal Scientist at Palo Alto Research Center's Augmented Social Cognition Group. He led the group in understanding how Web2.0 and Social Computing systems help groups of people to remember, think and reason. Ed completed his three degrees (B.S., M.S., and Ph.D.) in 6.5 years from University of Minnesota, and has been doing research on user interface software systems since 1993. He has been featured and quoted in the press, including the Economist, Time Magazine, LA Times, and the Associated Press.
With 20 patents and over 80 research articles, his most well-known past project is the study of Information Scent — understanding how users navigate and understand the Web and information environments. Most recently, he leads a group of researchers at PARC to understand the underlying mechanisms in online social systems such as Wikipedia and social tagging sites. He has also worked on information visualization, computational molecular biology, ubicomp, and recommendation/search engines. He has won awards for both teaching and research. In his spare time, Ed is an avid Taekwondo martial artist, photographer, and snowboarder.
CSCL 2011 Keynote on Social Computing and eLearningEd Chi
Ed H. Chi
Google Research (Work done at Xerox PARC)
CSCL2011 Keynote Abstract:
Our research in Augmented Social Cognition is aimed at enhancing the ability of a group of people to remember, think, and reason. Our approach to creating this augmentation or enhancement is primarily model-driven. Our system developments are informed by models such as information scent, sensemaking, information theory, probabilistic models, and more recently, evolutionary dynamic models. These models have been used to understand a wide variety of user behaviors, from individuals interacting with social bookmark search in Delicious and MrTaggy.com to groups of people working on articles in Wikipedia. These models range in complexity from a simple set of assumptions to complex equations describing human and group behaviors.
Indeed, increasingly, new social online resources such as social bookmarking sites and Wikis are becoming central in eLearning. By studying them, we further our understanding of how knowledge is constructed in a social context. In this talk, I will illustrate how a model-driven approach could help illuminate the path forward for social computing and social learning.
-----
Large Scale Social Analytics on Wikipedia, Delicious, and Twitter (presented ...Ed Chi
Ed H. Chi, Palo Alto Research Center
Large-Scale Social Analytics in Wikipedia, Delicious, and Twitter
Abstract
We will illustrate an analytical research approach in social computing. Our research in Augmented Social Cognition is aimed at enhancing the ability of a group of people to remember, think, and reason. The drive to build models and theories for social computing research should further our understanding of how network science, behavioral economics, and evolutionary theories could explain how social systems work. Here we will summarize the published research we conducted on large-scale social analytics in Wikipedia, Delicious, and Twitter, and point out how social analytics can help us understand the intricacies of large social systems.
About the Speaker
Ed H. Chi is area manager and principal scientist at Palo Alto Research Center's Augmented Social Cognition Group. He leads the group in understanding how Web2.0 and Social Computing systems help groups of people to remember, think and reason. Ed completed his three degrees (B.S., M.S., and Ph.D.) in 6.5 years from University of Minnesota, and has been doing research on user interface software systems since 1993. He has been featured and quoted in the press, such as the Economist, Time Magazine, LA Times, and the Associated Press. With 20 patents and over 70 research articles, he has won awards for both teaching and research. In his spare time, Ed is an avid Taekwondo martial artist, photographer, and snowboarder.
2010 June 13
Keynote talk given at the
Workshop for Modeling Social Media
ACM Hypertext 2010 Conference
Presenter: Ed H. Chi
Talk Title:
Model-driven Research for Augmenting Social Cognition
Short Abstract:
Model-driven research seeks to predict and to explain the phenomena in systems. The drive to do this for social computing research should further our understanding of how these systems evolve and develop. I will illustrate how we have modeled the dynamics in the popular social bookmarking system, Delicious, using Information Theory. I will also show how using equations from Evolutionary Dynamics we were better able to explain what might be happening to Wikipedia's contribution patterns.
Using Information Scent to Model Users in Web1.0 and Web2.0Ed Chi
This talk summarizes the work I have been doing on modeling user behavior on Web1.0 and Web2.0 systems in the last 13 years
Talk given at a workshop on Cognitive Modeling in Utrecht, Netherlands on March 20, 2010.
2010-03-10 PARC Augmented Social Cognition Research OverviewEd Chi
This is an overview of the 3-year research works done at the Augmented Social Cognition research group at PARC.
See blog at:
http://asc-parc.blogspot.com
2010-02-22 Wikipedia MTurk Research talk given in Taiwan's Academica SinicaEd Chi
This is the talk I gave at the Academica Sinica Inst. for Information Science in Taiwan. It focuses on our Wikipedia and Amazon Mechanical Turk research.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Unsubscribed: Combat Subscription Fatigue With a Membership Mentality by Head...
China HCI Symposium 2010 March: Augmented Social Cognition Research from PARC, by Ed H. Chi
1. Enhancing the Social Web through Augmented Social Cognition Research Ed H. Chi 紀懷新 , Area Manager Peter Pirolli, Lichan Hong, Bongwon Suh, Gregorio Convertino, Les Nelson, Rowan Nairn Augmented Social Cognition Area Palo Alto Research Center Interns: Sanjay Kairam, Jilin Chen, Michael Bernstein Alumni: Raluca Budiu, Bryan Pendleton, Niki Kittur, Todd Mytkowicz, Terrell Russell, Brynn Evans, Bryan Chan, KMRC students Image from: http://www.flickr.com/photos/ourcommon/480538715/ 2010-03-15 Ed H. Chi ASC Overview
9. Wikipedia Success is counter-intuitive “ Wikipedia is the best thing ever. Anyone in the world can write anything they want about any subject, so you know you’re getting the best possible information.” – Steve Carell, The Office 2010-03-15 Ed H. Chi ASC Overview
13. 2010-03-15 Ed H. Chi ASC Overview Characterization Models Prototypes Evaluations
14. Conflict/Coordination Effects in Wikipedia [Kittur et al., CHI2007] 2010-03-15 (joint work with Niki Kittur, Bongwon Suh, Bryan Pendleton) Ed H. Chi ASC Overview
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22. Opinions on Dokdo/Takeshima 2010-03-15 Ed H. Chi ASC Overview Group A Group B Group C Group D Number of users in user group A B C Total Users with Korean point of view 10 6 0 16 Users with Japanese point of view 1 8 7 16 Neutral or Unidentified 7 3 6 17
23. Mediator Pattern - Terri Schiavo Mediators Sympathetic to parents Sympathetic to husband Anonymous (vandals/spammers) 2010-03-15 Ed H. Chi ASC Overview
24. Ratio of Reverted Contribution Monthly Ratio of Reverted Edits 2010-03-15 Ed H. Chi ASC Overview
25. 2010-03-15 Ed H. Chi ASC Overview Characterization Models Prototypes Evaluations
26. Example: Modeling Wikipedia Growth Bongwon Suh, Gregorio Convertino, Ed H. Chi, Peter Pirolli 2010-03-15 Ed H. Chi ASC Overview Bongwon Suh, Gregorio Convertino, Ed H. Chi, Peter Pirolli. The Singularity is Not Near: Slowing Growth of Wikipedia. In Proc. of WikiSym 2009. Oct, 2009. Florida, USA
28. Slowing Growth in Global Activity Monthly Active Editors 2010-03-15 Ed H. Chi ASC Overview
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34. Using Information Theory to Model Social Tagging [Ed H. Chi, Todd Mytkowicz, ACM Hypertext 2008] Topics Users Documents Decoding 2010-03-15 Ed H. Chi ASC Overview Concepts Tags T 1 …T n Encoding Noise
36. H(Doc | Tag), browsability 2010-03-15 Ed H. Chi ASC Overview
37. I ( Doc ; Tag ) Mutual Information 2010-03-15 Ed H. Chi ASC Overview Source: Hypertext 2008 study on del.icio.us (Chi & Mytkowicz)
38. Raise in avg. tag per bookmark (note parallel the development in increasing # of query words) 2010-03-15 Ed H. Chi ASC Overview
39. Understanding a new area… 2010-03-15 Characterization Models Prototypes Evaluations Ed H. Chi ASC Overview
40. MrTaggy.com: social search browser with social bookmarks Joint work with Rowan Nairn, Lawrence Lee Kammerer, Y., Nairn, R., Pirolli, P., and Chi, E. H. 2009. Signpost from the masses: learning effects in an exploratory social tag search browser. In Proceedings of the 27th international Conference on Human Factors in Computing Systems (Boston, MA, USA, April 04 - 09, 2009). CHI '09. ACM, New York, NY, 625-634. 2010-03-15 Ed H. Chi ASC Overview
43. TagSearch: Use Semantic Analysis to Reduce Noise http://mrtaggy.com 2010-03-15 Ed H. Chi ASC Overview Guide Web Howto Tips Help Tools Tip Tricks Tutorial Tutorials Reference Semantic Similarity Graph
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46. Understanding a new area… 2010-03-15 Characterization Models Prototypes Evaluations Ed H. Chi ASC Overview
52. Living Laboratory: Prototyping Social Applications on the Internet Create a Living Laboratory as a platform to develop, test, and market innovations [HCIC workshop 2009, HCII 2009, IEEE Computer Sep/2008] 2010-03-15 Ed H. Chi ASC Overview
66. A way to think about these systems Voting systems Collaborative Co-Creation Col. Information Structures 2010-03-15 Ed H. Chi ASC Overview Naver Heavier collaboration Digg.com Wikipedia Slashdot eHow.com Del.icio.us IBM dogear PageRank Flickr
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68. WikiDashboard: Social Transparency for Wikipedia Joint work with Bongwon Suh, Aniket Kittur, Bryan Pendleton Bongwon Suh, Ed H. Chi, Aniket Kittur, Bryan A. Pendleton. Lifting the Veil: Improving Accountability and Social Transparency in Wikipedia with WikiDashboard. In Proceedings of the ACM Conference on Human-factors in Computing Systems (CHI2008). ACM Press, 2008. Florence, Italy. 2010-03-15 Ed H. Chi ASC Overview
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70. Top Editor - Wasted Time R 2010-03-15 Ed H. Chi ASC Overview
79. TagSearch Exploratory Focus 3 kinds of search 2010-03-15 Ed H. Chi ASC Overview navigational transactional 28% 13% You know what you want and where it is You know what you want to do Existing search engines are OK informational 59% You roughly know what you want but don’t know how to find it Difficult for existing search engines Opportunity
80. SparTag.us: Social Paragraph-level Tagging Joint work with Lichan Hong, Raluca Budiu, Les Nelson, Peter Pirolli Lichan Hong, Ed H. Chi, Raluca Budiu, Peter Pirolli, and Les Nelson. SparTag.us: A Low Cost Tagging System for Foraging of Web Content. In Proceedings of the Advanced Visual Interface (AVI2008), (to appear). ACM Press, 2008 . 2010-03-15 Ed H. Chi ASC Overview
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84. Duplicate Content via Paragraph Fingerprinting [Hong and Chi, CHI2009] 2010-03-15 Ed H. Chi ASC Overview
85. My Reading Notebook 2010-03-15 Ed H. Chi ASC Overview
86. Social Sharing friend’s tags my tags my highlights friend’s highlights 2010-03-15 Ed H. Chi ASC Overview
88. Experimental Evaluation: Significant Learning Gain N=18 SparTag.us + Friend superior to both individual conditions No difference between the two controls [Nelson et al., CHI2009] 2010-03-15 Ed H. Chi ASC Overview Without SparTag.us (WS) SparTag.us Only (SO) SparTag.us With A Friend (SF) SF group, M=0.46, SD=0.22 SO group, M=0.13, SD=0.32 WS group, M=0.27, SD=0.23
Editor's Notes
PARC FORUM *this week*: Thursday May 1, 4:00 – 5:00 pm, George E. Pake Auditorium at Palo Alto Research Center (www.parc.com/directions) TITLE: "Enhancing the Social Web through Augmented Social Cognition research" SPEAKER: Ed Chi, PARC Augmented Social Cognition group ABSTRACT: We are experiencing the new Social Web, where people share, communicate, commiserate, and conflict with each other. As evidenced by Wikipedia and del.icio.us, Web 2.0 environments are turning people into social information foragers and sharers. Users interact to resolve conflicts and jointly make sense of topic areas from “Obama vs. Clinton” to “Islam.” PARC‘s Augmented Social Cognition researchers -- who come from cognitive psychology, computer science, HCI, sociology, and other disciplines -- focus on understanding how to “enhance a group of people’s ability to remember, think, and reason”. Through Web 2.0 systems like social tagging, blogs, Wikis, and more, we can finally study, in detail, these types of enhancements on a very large scale. In this Forum, we summarize recent PARC work and early findings on: (1) how conflict and coordination have played out in Wikipedia, and how social transparency might affect reader trust; (2) how decreasing interaction costs might change participation in social tagging systems; and (3) how computation can help organize user-generated content and metadata. ABOUT THE SPEAKER: Ed H. Chi is a senior research scientist and area manager of PARC's Augmented Social Cognition group. His previous work includes understanding Information Scent (how users navigate and make sense of information environments like the Web), as well as developing information visualizations such as the "Spreadsheet for Visualization" (which allows users to explore data through a spreadsheet metaphor where each cell holds an entire data set with a full-fledged visualization). He has also worked on computational molecular biology, ubiquitous computing systems, and recommendation and personalized search engines. Ed has over 19 patents and has been conducting research on user interface software systems since 1993. He has been quoted in the Economist, Time Magazine, LA Times, Slate, and the Associated Press. Ed completed his B.S., M.S., and Ph.D. degrees from the University of Minnesota between 1992 and 1999. In his spare time, he is an avid Taekwondo black belt, photographer, and snowboarder. *************************************************** This is the final talk in our "Going Beyond Web 2.0" speaker series. Previous talks in this series, as well as other recent Forum talks, are available online at www.parc.com/forums. ************************************************** To subscribe to future PARC Forum announcements and/or our bimonthly e-newsletter, please visit: www.parc.com/subscriptions. To unsubscribe from Forum announcements, please send an e-mail to info@parc.com specifying the e-mail address you'd like to have removed.
This clip is from a comedy show, but it raises a serious question as well. What does happen when you have millions of people with different viewpoints all editing the same content? Well, you get a lot of conflict. I’m going to briefly go through an example of conflict that occurred on one of the most heavily edited pages in Wikipedia, which is, <pause>, you guessed it, about our own George W .
In the enterprise, these have become the standard set of Web 2.0 tools in practice. They have several benefits – they can be set up by end users without needing IT, they have familiar UIs from consumer versions, And in terms of knowledge sharing, an important advantage these tools have over traditional KM systems is that knowledge can be captured and archived through the act of communication without requiring extra work by users. These tools will become increasingly important in the office as younger people enter the workforce and expect to be able to use them.
Paste controversial tag picture here Figure depicting CRC
Selected a set of page metrics which we could scale to compute across large numbers of pages.
This graph is just running the model on the list of controversial topics, it is not x-validation. It’s R-square is actually 0.897.
This graph is just running the model on the list of controversial topics, it is not x-validation. It’s R-square is actually 0.897.
Especially interesting: unique editors DECREASE conflict. Anonymous edits are bad when on the discussion page but not the article page. Change to 1,2,3,4... and up/down arrows
1m
Year 2013, <10k new articles per month is expected to be added. Knowledge does not stop growing!
Therefore, this is the model that we suggest!
There are really two facets of tagging. The first is encoding: when you encounter a document, have read or skimmed it and have to generate a few words that describe it. The second side of tagging is retrieval: you find a new document that has several tags attached to it, and you read those tags and the document. The tags may give you an idea about what the document is about. I am going to come back to this distinction later.
Vocabulary saturation! shows a marked increase in the entropy of the tag distribution H(T) up until week 75 (mid-2005) at which point the entropy measure hits a plateau. Since the total number of tags keeps increasing, tag entropy can only stay constant in the plateau by having the tag probability distribution become less uniform. What this suggests is that users are having a hard time coming up with “unique” tags. That is to say, a user is more likely to add a tag to del.icio.us that is already popular in the system, than to add a tag that is relatively obscure.
What’s perhaps the most telling data of all is the entropy of documents conditional on tags, H(D|T) , which is increasing rapidly (see Figure 4). What this means is that, even after knowing completely the value of tags, the entropy of the document is still increasing. Conditional Entropy asks the question: “Given that I know a set of tags, how much uncertainty regarding the document set that I was referencing with those tags remains?” This measure gives us a method for analyzing how useful a set of tags is at describing a document set. The fact that this curve is strictly increasing suggests that the specificity of any given tag is decreasing. That is to say, as a navigation aid, tags are becoming harder and harder to use. We are moving closer and closer to the proverbial “needle in a haystack” where any single tag references too many documents to be considered useful.
Figure 6 shows the number of tags per bookmark over time. The trend is clearly increasing, complementing the increase in navigation difficulty.
In the enterprise, these have become the standard set of Web 2.0 tools in practice. They have several benefits – they can be set up by end users without needing IT, they have familiar UIs from consumer versions, And in terms of knowledge sharing, an important advantage these tools have over traditional KM systems is that knowledge can be captured and archived through the act of communication without requiring extra work by users. These tools will become increasingly important in the office as younger people enter the workforce and expect to be able to use them.
As I browse the web and annotate the pages, one of the things that SparTag.us automatically created for me is a notebook which contains all the paragraphs that I have annotated. Here it shows when I annotated this paragraph. Here is an option that allows me to make my annotations on this paragraph become private. Here are the URLs that I have visited and contain this paragraph. And I can search my notebook against the tags that I specified, the text that I highlighted, the text of the paragraphs that I annotated, or the URLs. By the way, this last one was suggested by Prateek who was a subject in our last user study. And here is a tag cloud which is really a representation of what kind of keywords I have using as tags.
Posing the right questions is half of the work.
Voting systems: faddishness of information, social dashboards Col info. Structures: explicit social networks Collaborative Co-creation
Voting systems: faddishness of information, social dashboards Col info. Structures: explicit social networks Collaborative creation
In other words, a person did not see both a high-trust and low-trust visualization for the same page.
Remember, our goal is not to see whether they noticed the visualization or not, but how much impact it could have.
So we ran two parts of the experiment, here are the combined results. Notice two things: Huge effect No significant interactions – trust was impacted Bi-directional change in trust: increase over baseline and decrease below baseline
Informational search – ambiguity in query – where social search has most power
What is the valuable problem addressed by this research program? What is the target (user, company, application, market), what is our place in the value chain, and what is the business model to bring value to the target and PARC?
As you can tell from my demo, what is being tagged are paragraphs. This is based on our intuition that although there are cases where it makes sense to tag the whole document, there are many other cases where the interesting nuggets of information are at the sub-document level, for example, entities, facts, concepts, and paragraphs. Our implementation focuses on paragraphs for now. The key idea is that we compute a unique fingerprint for each paragraph that we encounter. Currently, we use Secure Hash Algorithm to compute the paragraph fingerprint. We are exploring other ways in the future. This simple idea of paragraph fingerprint has also been picked up by other projects in UbiDocs.
Here is an example of duplicate content. Here we have a story at Forbes.com which is about the recent tragedy happening in Minnesota and I annotated part of the story. Here on a different web site, the same story appears and my annotations show up too.
As I browse the web and annotate the pages, one of the things that SparTag.us automatically created for me is a notebook which contains all the paragraphs that I have annotated. Here it shows when I annotated this paragraph. Here is an option that allows me to make my annotations on this paragraph become private. Here are the URLs that I have visited and contain this paragraph. And I can search my notebook against the tags that I specified, the text that I highlighted, the text of the paragraphs that I annotated, or the URLs. By the way, this last one was suggested by Prateek who was a subject in our last user study. And here is a tag cloud which is really a representation of what kind of keywords I have using as tags.
The way that we support social sharing is through a simple user interface like this. Here I designate myself as a fan of Ed, which means that I can see his annotations. When I go to this web page, I see that Ed has been here before and decided to leave some annotations. Of course, I can highlight or tag this paragraph too. Now, if I don’t want to be Ed’s fan anymore, I can remove his name from my friend list. And his annotations disappear too. And because this is done in AJAX, there is no need to reload the page.
A nice thing about SparTag.us is that when you come to a web page, it sort of tells you what may be interesting to pay attention to. Here it reminds me that these are two paragraphs that I have annotated. Here I see that Ed has annotated this paragraph.