A comparative study of bloggers linking to professional and participatory media. Do bloggers refer to a broad range of viewpoints and do they evaluate and comment on linked material? Through a combined content and network analysis of 323 blogs, this study reveals that bloggers primarily give attention to a small selection of articles on a given topical basis.
In online social media platforms, users can express their ideas by posting original content or by adding comments and responses to existing posts, thus generating virtual discussions and conversations. Studying these conversations is essential for understanding the online communication behavior of users. This study proposes a novel approach to retrieve popular patterns on online conversations using network-based analysis. The analysis consists of two main stages: intent analysis and network generation. Users’ intention is detected using keyword-based categorization of posts and comments, integrated with classification through Naïve Bayes and Support Vector Machine algorithms for uncategorized comments. A continuous human-in-the-loop approach further improves the keyword-based classification. To build and understand communication patterns among the users, we build conversation graphs starting from the hierarchical structure of posts and comments, using a directed multigraph network. The experiments categorize 90% comments with 98% accuracy on a real social media dataset. The model then identifies relevant patterns in terms of shape and content; and finally determines the relevance and frequency of the patterns. Results show that the most popular online discussion patterns obtained from conversation graphs resemble real-life interactions and communication.
2010 Catalyst Conference - Trends in Social Network AnalysisMarc Smith
Review of trends related to social network analysis in the enterprise. Presented at the 2010 Catalyst Conference in San Diego, CA july 29, 2010. Presented with Mike Gotta, Gartner Group.
Least Cost Influence by Mapping Online Social Networks paperpublications3
Abstract: The online social network has become popular for sharing the information. Online social networks exhibit many platforms to create awareness of new products. In recent time Least cost Influence problem to find minimum number of seed user is most important topic in online social networks. The eventual target is to find the least advertising cost set of users which produce enormous influence. In existing many diffusion models are used. In this paper the stochastic threshold model is used to find the seed user in multiple online social networks to maximize the influence. This model decreases the processing time comparing to the other models.
Keywords: Stochastic threshold model, influence, diffusion, multiple networks, online social networks.
Title: Least Cost Influence by Mapping Online Social Networks
Author: Bessmitha S, Shajini N
ISSN 2350-1022
International Journal of Recent Research in Mathematics Computer Science and Information Technology
Paper Publications
In online social media platforms, users can express their ideas by posting original content or by adding comments and responses to existing posts, thus generating virtual discussions and conversations. Studying these conversations is essential for understanding the online communication behavior of users. This study proposes a novel approach to retrieve popular patterns on online conversations using network-based analysis. The analysis consists of two main stages: intent analysis and network generation. Users’ intention is detected using keyword-based categorization of posts and comments, integrated with classification through Naïve Bayes and Support Vector Machine algorithms for uncategorized comments. A continuous human-in-the-loop approach further improves the keyword-based classification. To build and understand communication patterns among the users, we build conversation graphs starting from the hierarchical structure of posts and comments, using a directed multigraph network. The experiments categorize 90% comments with 98% accuracy on a real social media dataset. The model then identifies relevant patterns in terms of shape and content; and finally determines the relevance and frequency of the patterns. Results show that the most popular online discussion patterns obtained from conversation graphs resemble real-life interactions and communication.
2010 Catalyst Conference - Trends in Social Network AnalysisMarc Smith
Review of trends related to social network analysis in the enterprise. Presented at the 2010 Catalyst Conference in San Diego, CA july 29, 2010. Presented with Mike Gotta, Gartner Group.
Least Cost Influence by Mapping Online Social Networks paperpublications3
Abstract: The online social network has become popular for sharing the information. Online social networks exhibit many platforms to create awareness of new products. In recent time Least cost Influence problem to find minimum number of seed user is most important topic in online social networks. The eventual target is to find the least advertising cost set of users which produce enormous influence. In existing many diffusion models are used. In this paper the stochastic threshold model is used to find the seed user in multiple online social networks to maximize the influence. This model decreases the processing time comparing to the other models.
Keywords: Stochastic threshold model, influence, diffusion, multiple networks, online social networks.
Title: Least Cost Influence by Mapping Online Social Networks
Author: Bessmitha S, Shajini N
ISSN 2350-1022
International Journal of Recent Research in Mathematics Computer Science and Information Technology
Paper Publications
Community analysis using graph representation learning on social networksMarco Brambilla
In a world more and more connected, new and complex interaction
patterns can be extracted in the communication between people.
This is extremely valuable for brands that can better understand
the interests of users and the trends on social media to better target
their products. In this paper, we aim to analyze the communities
that arise around commercial brands on social networks to understand
the meaning of similarity, collaboration, and interaction
among users.We exploit the network that builds around the brands
by encoding it into a graph model.We build a social network graph,
considering user nodes and friendship relations; then we compare
it with a heterogeneous graph model, where also posts and hashtags
are considered as nodes and connected to the different node
types; we finally build also a reduced network, generated by inducing
direct user-to-user connections through the intermediate
nodes (posts and hashtags). These different variants are encoded
using graph representation learning, which generates a numerical
vector for each node. Machine learning techniques are applied to
these vectors to extract valuable insights for each user and for the
communities they belong to. In the paper, we report on our experiments
performed on an emerging fashion brand on Instagram, and
we show that our approach is able to discriminate potential customers
for the brand, and to highlight meaningful sub-communities
composed by users that share the same kind of content on social
networks.
Social Network Analysis (SNA) and its implications for knowledge discovery in...ACMBangalore
Social Network Analysis (SNA) and its implications for knowledge discovery in Informal Networks- Talk by Dr Jai Ganesh, SETLabs, Infosys at Search and Social Platforms tutorial, as part of Compute 2009, ACM Bangalore
Social Network Analysis: What It Is, Why We Should Care, and What We Can Lear...Xiaohan Zeng
The advent of the social networks has completely changed our daily life. The deluge of data collected on Social Network Services (SNS) and recent developments in complex network theory have enabled many marvelous predictive analysis, which tells us many amazing stories.
Why do we often feel that "the world is so small?" Is the six-degree separation purely imagination or based on mathematical insights? Why are there just a few rockstars who enjoy extreme popularity while most of us stay unknown to the world? When science meets coffee shop knowledge, things are bound to be intriguing.
I will first briefly describe what social networks are, in the mathematical sense. Then I will introduce some ways to extract characteristics of networks, and how these analyses can explain many anecdotes in our life. Finally, I'll show an example of what we can learn from social network analysis, based on data from Groupon.
A presentation describing application of Node XL into analyzing social networks.
Made as part of project work for ITB course at VGSOM IIT Kharagpur.
By : Mayank Mohan
Anuradha Chakraborty
( Batch of 2012)
Expectations for Electronic Debate Platforms as a Function of Application DomainIJERA Editor
Electronic debate (or commenting) platforms are used with many types of online applications, as a way to engage the users or to provide enhancements, e.g., based on some type of collaborative filtering [1], [2]. The applications enhanced with such debate platforms range widely : news, products, sport, religion, politics, etc. Therefore, the emerging question is whether it is possible to make one electronic debate mechanism good for all applications, and whether the studies on the success of a debate mechanism in one domain do automatically apply to other application domains. Here we compare two traditional application domains of electronic debate platforms: product evaluation and commented news. We exploit the fact that most users are very familiar with both types of such applications, and therefore surveys can be designed to gauge reliably subtle differences between expectations and properties of these domains. Based on over 1000 responses to surveys described here, we are able to report statistically significant differences between the user behavior and expectations in the studied domains.
LAK13 Tutorial Social Network Analysis 4 Learning Analyticsgoehnert
Slides of the tutorial "Computational Methods and Tools for Social Network Analysis Networked Learning Communities" at the LAK 2013 in Leuven.
Tutorial Homepage:
http://snatutoriallak2013.ku.de/index.php/SNA_tutorial_at_LAK_2013
Conference Homepage:
http://lakconference2013.wordpress.com/
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/
Community analysis using graph representation learning on social networksMarco Brambilla
In a world more and more connected, new and complex interaction
patterns can be extracted in the communication between people.
This is extremely valuable for brands that can better understand
the interests of users and the trends on social media to better target
their products. In this paper, we aim to analyze the communities
that arise around commercial brands on social networks to understand
the meaning of similarity, collaboration, and interaction
among users.We exploit the network that builds around the brands
by encoding it into a graph model.We build a social network graph,
considering user nodes and friendship relations; then we compare
it with a heterogeneous graph model, where also posts and hashtags
are considered as nodes and connected to the different node
types; we finally build also a reduced network, generated by inducing
direct user-to-user connections through the intermediate
nodes (posts and hashtags). These different variants are encoded
using graph representation learning, which generates a numerical
vector for each node. Machine learning techniques are applied to
these vectors to extract valuable insights for each user and for the
communities they belong to. In the paper, we report on our experiments
performed on an emerging fashion brand on Instagram, and
we show that our approach is able to discriminate potential customers
for the brand, and to highlight meaningful sub-communities
composed by users that share the same kind of content on social
networks.
Social Network Analysis (SNA) and its implications for knowledge discovery in...ACMBangalore
Social Network Analysis (SNA) and its implications for knowledge discovery in Informal Networks- Talk by Dr Jai Ganesh, SETLabs, Infosys at Search and Social Platforms tutorial, as part of Compute 2009, ACM Bangalore
Social Network Analysis: What It Is, Why We Should Care, and What We Can Lear...Xiaohan Zeng
The advent of the social networks has completely changed our daily life. The deluge of data collected on Social Network Services (SNS) and recent developments in complex network theory have enabled many marvelous predictive analysis, which tells us many amazing stories.
Why do we often feel that "the world is so small?" Is the six-degree separation purely imagination or based on mathematical insights? Why are there just a few rockstars who enjoy extreme popularity while most of us stay unknown to the world? When science meets coffee shop knowledge, things are bound to be intriguing.
I will first briefly describe what social networks are, in the mathematical sense. Then I will introduce some ways to extract characteristics of networks, and how these analyses can explain many anecdotes in our life. Finally, I'll show an example of what we can learn from social network analysis, based on data from Groupon.
A presentation describing application of Node XL into analyzing social networks.
Made as part of project work for ITB course at VGSOM IIT Kharagpur.
By : Mayank Mohan
Anuradha Chakraborty
( Batch of 2012)
Expectations for Electronic Debate Platforms as a Function of Application DomainIJERA Editor
Electronic debate (or commenting) platforms are used with many types of online applications, as a way to engage the users or to provide enhancements, e.g., based on some type of collaborative filtering [1], [2]. The applications enhanced with such debate platforms range widely : news, products, sport, religion, politics, etc. Therefore, the emerging question is whether it is possible to make one electronic debate mechanism good for all applications, and whether the studies on the success of a debate mechanism in one domain do automatically apply to other application domains. Here we compare two traditional application domains of electronic debate platforms: product evaluation and commented news. We exploit the fact that most users are very familiar with both types of such applications, and therefore surveys can be designed to gauge reliably subtle differences between expectations and properties of these domains. Based on over 1000 responses to surveys described here, we are able to report statistically significant differences between the user behavior and expectations in the studied domains.
LAK13 Tutorial Social Network Analysis 4 Learning Analyticsgoehnert
Slides of the tutorial "Computational Methods and Tools for Social Network Analysis Networked Learning Communities" at the LAK 2013 in Leuven.
Tutorial Homepage:
http://snatutoriallak2013.ku.de/index.php/SNA_tutorial_at_LAK_2013
Conference Homepage:
http://lakconference2013.wordpress.com/
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/
The Power of Platforms - Inaugural lecture by Rasmus Kleis Nielsen, U of OxfordRasmus Kleis Nielsen
Platform companies like Facebook, Google, Twitter and others like them are amongst the driving forces in a profound transformation of our societies. This lecture focuses on the distinct forms of “platform power” that they exercise. It identifies five key aspects of platform power (standards, connections, automated action at scale, secrecy, and fungibility) and show how platform power is profoundly enabling, transformative, and productive, animated by how platforms empower other actors while also making them more dependent. Platform power is deeply relational and not a sovereign power that platform companies possess and can use at their pleasure—but it is a form of power nonetheless, tied to the institutional and strategic interests of platform companies themselves, and driving a structural transformation in our media environment and political life.
A multifaceted study of online news diversity: issues and methodssmyrnaios
Emmanuel Marty, Nikos Smyrnaios and Franck Rebillard
In Ramón Salaverría (ed.), Diversity of Journalisms, Proceedings of the ECREA Journalism Studies Section and 26th International Conference of Communication (CICOM) at University of Navarra, Pamplona, 4-5 July 2011, p. 228-242
Design Matters! An Empirical Analysis of Online Deliberation on Different New...Katharina Esau
Ever since the internet has provided easy access to online debates, advocates of deliberative democracy have hoped for an improved public sphere. This paper investigates which particular platform features promote deliberative debate online. We assume that moderation, asynchronous discussion, a well-defined topic, and the availability of information enhance
the level of deliberative quality of user comments. A comparison between different types of news platforms that differ in terms of design (a news forum, news websites, and Facebook news pages) shows that deliberation (rationality, reciprocity, respect, and constructiveness) differs significantly between platforms. The news forum yields the most rational and respectful debate. While user comments on news websites are only slightly less
deliberative, Facebook comments perform poorly in terms of deliberative quality. However, comments left on news websites and on Facebook show particularly high levels of reciprocity among users.
Innovative approaches to analyses of online social networksJakob Jensen
This is the introduction to our panel from Association of Internet Researchers' conference IR13 in Salford, Oct 18th-21th 2012. It contains my introduction to the panel + my own presentation on a framework for online social network analysis. Enjoy!
Generative models of online discussion threads (ASONAM 2018 tutorial)Pablo Aragón
Online discussion is a core feature of numerous social media platforms and has attracted increasing attention from academia for different and relevant reasons, e.g., the resolution of problems in collaborative editing, question answering and e-learning platforms, the response of online communities to news events, online political and civic participation, etc. Discussions on the Internet commonly occur as a exchange of written messages among two or more participants. These conversations are often represented as threads, which are initiated by a user posting a starting message (a post) and then other users replies to either the post or the earlier replies. Given this sequential posting behavior, online discussion threads follow a tree network structure.
Different modeling approaches have been proposed to identify the governing mechanisms of the network structure of threads. Statistical models of this type are aimed to reproduce the growth of discussion threads through different features, often related to human behavior. This is why they are usually called generative models: they do not only estimate the statistical significance of their corresponding features but also reproduce the temporal arrival patterns of messages that form a discussion thread. The parameters of these models allow to compare different platforms and communities, they even can help to assess the impact of design choices and user interface changes on the way the discussions unfold. Therefore, we aim to provide the participants with state of the art tools and methods for the analysis, diagnosis, management and improvement of online discussion platform and communities.
Horizontal communication and the evolution of journalismDonica Mensing
Presentation given at "Networking Democracy? New media innovations in participatory politics" in Cluj-Napoca, Romania, June 2010.
This project uses an examination of Twitter and Facebook posts about climate change to consider how horizontal communication structures are changing journalistic practices, and in turn, affecting the creation of public agendas.
Visual Analysis of Topic Competition on Social Media Yingcai Wu
How do various topics compete for public attention when they are spreading on social media? What roles do opinion leaders play in the rise and fall of competitiveness of various topics? In this study, we propose an expanded topic competition model to characterize the competition for public attention on multiple topics promoted by various opinion leaders on social media. To allow an intuitive understanding of the estimated measures, we present a timeline visualization through a metaphoric interpretation of the results. The visual design features both topical and social aspects of the information diffusion process by compositing ThemeRiver with storyline style visualization. ThemeRiver shows the increase and decrease of competitiveness of each topic. Opinion leaders are drawn as threads that converge or diverge with regard to their roles in influencing the public agenda change over time. To validate the effectiveness of the visual analysis techniques, we report the insights gained on two collections of Tweets: the 2012 United States presidential election and the Occupy Wall Street movement.
The slide deck was made by Panpan Xu and presented by her in IEEE VAST 2013.
More details about this project can be found from the project page:
http://www.ycwu.org/projects/vast13.html
ICA 2012: User recommendations for journalistic websites on Twitter Christian Nuernbergk
User recommendations for journalistic websites on Twitter (ICA Presentation 2012, Phoenix)
Hanna Jo vom Hofe, Christian Nuernbergk, Christoph Neuberger
siehe Neuberger/vom Hofe/Nuernbergk (2010): "Journalismus und Twitter. Der Einfluss des 'Social Web' auf die Nachrichten" Düsseldorf: Landesanstalt für Medien Nordrhein-Westfalen (=LfM-Dokumentation Nr. 38)
Chancen einer integrierten Oeffentlichkeit? Vernetzter Journalismus im „Web ...Christian Nuernbergk
Journalismus in einer digitalen Welt - Prognosen, Erwartungen, FragenFachtagung des Vereins zur Förderung der ZeitungsforschungDortmund, 18. Juni 2010
Christian Nuernbergk (Westfälische Wilhelms-Universität Münster)
‘वोटर्स विल मस्ट प्रीवेल’ (मतदाताओं को जीतना होगा) अभियान द्वारा जारी हेल्पलाइन नंबर, 4 जून को सुबह 7 बजे से दोपहर 12 बजे तक मतगणना प्रक्रिया में कहीं भी किसी भी तरह के उल्लंघन की रिपोर्ट करने के लिए खुला रहेगा।
An astonishing, first-of-its-kind, report by the NYT assessing damage in Ukraine. Even if the war ends tomorrow, in many places there will be nothing to go back to.
01062024_First India Newspaper Jaipur.pdfFIRST INDIA
Find Latest India News and Breaking News these days from India on Politics, Business, Entertainment, Technology, Sports, Lifestyle and Coronavirus News in India and the world over that you can't miss. For real time update Visit our social media handle. Read First India NewsPaper in your morning replace. Visit First India.
CLICK:- https://firstindia.co.in/
#First_India_NewsPaper
03062024_First India Newspaper Jaipur.pdfFIRST INDIA
Find Latest India News and Breaking News these days from India on Politics, Business, Entertainment, Technology, Sports, Lifestyle and Coronavirus News in India and the world over that you can't miss. For real time update Visit our social media handle. Read First India NewsPaper in your morning replace. Visit First India.
CLICK:- https://firstindia.co.in/
#First_India_NewsPaper
31052024_First India Newspaper Jaipur.pdfFIRST INDIA
Find Latest India News and Breaking News these days from India on Politics, Business, Entertainment, Technology, Sports, Lifestyle and Coronavirus News in India and the world over that you can't miss. For real time update Visit our social media handle. Read First India NewsPaper in your morning replace. Visit First India.
CLICK:- https://firstindia.co.in/
#First_India_NewsPaper
El Puerto de Algeciras continúa un año más como el más eficiente del continente europeo y vuelve a situarse en el “top ten” mundial, según el informe The Container Port Performance Index 2023 (CPPI), elaborado por el Banco Mundial y la consultora S&P Global.
El informe CPPI utiliza dos enfoques metodológicos diferentes para calcular la clasificación del índice: uno administrativo o técnico y otro estadístico, basado en análisis factorial (FA). Según los autores, esta dualidad pretende asegurar una clasificación que refleje con precisión el rendimiento real del puerto, a la vez que sea estadísticamente sólida. En esta edición del informe CPPI 2023, se han empleado los mismos enfoques metodológicos y se ha aplicado un método de agregación de clasificaciones para combinar los resultados de ambos enfoques y obtener una clasificación agregada.
#FOJ2013 Follow-up communication in the blogosphere
1. Future of Journalism Conference 2013
Cardiff, September 12th 2013
FOLLOW-UP COMMUNICATION
IN THE BLOGOSPHERE
A comparative study of bloggers linking to
professional and participatory media
Dr. Christian Nuernbergk
2. Analysis of structural constraints to the public sphere under the
conditions of new media enabling “self-government”
The “networked public sphere”
Benkler (2006): Network structures on the Internet exhibit an ordered
system of filtering, intake and synthesis
Critiques about democratising effects and openness remain:
fragmentation (Sunstein, 2007) vs. concentration (Hindman, 2009)
New emerging news production models and opportunities for user
contributions
Professional and participatory media; complementarity rather than
competition (Neuberger & Nuernbergk, 2010)
public follow-up communication: “networked conversation“?
Cooperative mode and decentralised peer-review?
3. ► Follow-up Communication on the Internet
Traditional concept: interpersonal communication which relies on mass
media content, therefore making mass communication a primary subject in
discussions (Sommer, 2010; Eble, 2012).
Network-based media allows follow-up communication to become publicly
mediated; “public mode of interpersonal communication“ (Haas/Brosius, 2011)
(More) transparency regarding user’s preferences and contents: abilities
to connect and to contribute combined with observability, searchability, and
replicability of social media postings
Collaborative filtering as a result of networked content (Benkler, 2006;
Schmidt 2011)
Selectivity and content diversity of public follow-up communication:
Adding, or reinterpreting information? (Reese et al. 2007; Xenos 2008)
Openness of follow-up communication structures: Dynamics in the
contributors‟ network? (Nahon, 2011)
4. An approach for empirically testing differences and similarities by comparing
media coverage and related communication in network-based citizen media:
Transparency: Which actors and issues are made visible in professional mainstream
media and in network-based citizen media?
Validation: Do discourses correspond among professional media and network-based
citizen media? Which differences can be found regarding specific issues (evaluation of
sources, attributions, framing)?
Social navigation: How interconnected are professional media and citizen media
through linking patterns and other marked referrals to each other (e. g. citing sources
or other contributors‟ views)?
Identity formation: What kind of collective identity formation can be observed? How do
contributors in network-based media express and communicate differences to
professional media in their coverage?
► Dimensions for an examination of filter mechanisms
in the networked public-sphere:
5. Research Questions: “Follow-up Communication in the Blogosphere”
RQ1: What kind of network structure describes the follow-up communication
induced by professional and participatory news media in the
blogosphere?
RQ2: What kind of bloggers select, comment and link to professional and
participatory content?
7. Selected Issue: G8-Summit Heiligendamm
Contested political occasion (“counter-issue“ with several demonstrations);
high relevance and newsworthiness (main media event)
Clear time frames and good searchability
Increase of media-related participation and resonance in the social web discussing
this issue
Method: combining content analysis and network analysis:
In focus: Online press coverage, which induces follow-up communication in the
blogosphere
Selected time period: two weeks around the summit (May 28th to June 10th, 2007)
A related study researching print media (Rucht & Teune, 2008) offers possibilities to
compare online and offline differences
8. ► Internal and external networks of follow-up communication
Indymedia
Spiegel
Online
(external) network border
Blogs
9. Determination of relevant units through a hybrid selection process
Keyword: „Heiligendamm“ (issue-centred selection)
Identification of relevant articles in the archives of Spiegel Online and Indymedia
(media-centred selection)
Creating a archive-based list with specific URLs to each article
Collection and saving of all articles with LexiURL Linklist Analyser (Wolverhampton
Cybermetrics Group, Mike Thelwall)
Transformation of all URLs into automated search requests by using LexiURL
and the blog search engine Technorati (see Thelwall & Hasler 2007; Bruns 2007; Erlhofer 2010)
Open identification of follow-up communication for each URL; reflection of search
behaviour
All result lists generated by Technoraty were archived with LexiURL
Crawling of outlinks on these lists (= results referring to blog posts) and final
collection of all relevant 423 postings for content analysis procedures.
10. ► Findings (RQ1)
Blog Postings per Day
(in percent, shares for each network cluster„s follow-up communication identified in the time period from 28th May to
29th 2007, content analysis 2007)
0%
2%
4%
6%
8%
10%
12%
14%
16%
18%
nur Spiegel Online-Anschlusskomm. (n=247)
nur Indymedia-Anschlusskomm. (n=104)
gemeinsame Anschlusskomm. (Spiegel Online
und Indymedia verlinkt) (n=70)
Only reactions to Spiegel Online-articles (n=247)
Only reactions to Indymedia-articles (n=104)
Shared reactions (blog postings linking to articles
of Spiegel Online as well as Indymedia) (n=70)
Phasis of late-
following
reactions in
blogposts after
11th June
Time period
Number of
nodes
Share in
% (n=323)
Growth
in %*
Number of
edges
Share in
% (n=115)
Growth
in %*
28.05.-29.05.2007 13 4,0 4,0 0 0 0
30.05.-31.05.2007 35 10,9 6,9 2 1,7 1,7
01.06.-02.06.2007 71 22,0 11,1 7 6,1 4,4
03.06.-04.06.2007 130 40,3 18,3 21 18,3 12,2
05.06.-06.06.2007 199 61,6 21,3 68 59,1 40,8
11. # 1125.01.2012 # 1125.01.2012
Institut für Kommunikationswissenschaft und Medien-
forschung
Forschungs- und Lehrbereich Neuberger
Network of all identified and analysed blogs which link
to relevant articles of Spiegel Online or Indymedia
(325 nodes, 477 edges)
Three clusters
green: only reactions to Indymedia
red: only reactions to Spiegel Online
blue: shared reactions
„Networked conversation?“
► Findings (RQ1)
Network of Follow-up
Communication
12. ► Findings (RQ1)
Network of Follow-up
Communication (only Reactions)
Identified link connections among
contributing blogs
(323, nodes, 115 edges)
Three clusters
green: only reactions to Indymedia
red: only reactions to Spiegel Online
blue: shared reactions
13. Coverage Follow-up Communication
Main topic of article/posting Spiegel Online
(n=184)
Indymedia
(n=265)
Spiegel
Online- only
(n=246)
Indymedia-
only
(n=104)
Shared
reactions
(n=70)
Total
(n=420)
Protest (in general) 33 61 23 54 24 31
Security measures/
Police violence at protests
14 22 21 25 37 25
G8-summit happenings (in general) 11 1 12 5 0 8
Government’s arguments 7 0 3 0 0 2
Protestors’ arguments 7 2 1 0 1 1
Globalisation (in focus) 4 0 2 0 1 1
Climate change (in focus) 13 0 5 0 1 3
Media coverage
about event or related protests
4 6 25 14 30 23
Other focus 8 8 9 2 4 6
Cramer’s-V= .357, p< .001
►Results (RQ 1):
Main topics in the coverage of Indymedia, Spiegel Online and in the sample of their
follow-up communication in blogs (in %)
14. Type of external link destination
Spiegel Online-
only (n=972)
Indymedia-only
(n=415)
Shared reactions
(n=540)
Total
(n=1927)
Professional-edited news sites
(in affiliation with traditional media)
38,6 29,2 34,6 35,4
Professional-edited news sites (Internet-only) 3,6 4,1 6,9 4,6
Community-edited news sites 1,5 0,7 0,9 1,2
Weblogs (external), Twitter (linked accounts) 17,2 18,6 23,5 19,3
Protest websites 13,9 24,3 15,4 16,6
Governmental websites, political parties, public
administration and police websites
3,4 4,1 3,5 3,6
Justice (court websites) 0,7 0,7 0,6 0,7
Associations, unions 1,1 0,0 1,3 0,9
Main Internet portals, search engines 11,8 13,3 9,1 11,4
Other websites 8,1 5,1 4,3 6,4
Manual calculation. n-values comprise all external links (including multiple relations if more than one posting from an analysed blog linked to same external destination)
►Results (RQ 1):
Outgoing links: share of external destination types resulting from network clusters in
the follow-up communication (in %)
15. ►Results (RQ 1):
Popular links in the follow-up communication blog network
(sorted by Indegree, network analysis)
64
34
34
27
26
25
24
19
19
17
16
16
15
15
15
13
13
13
12
12
11
10
9
9
9
9
9
0 20 40 60 80
de.wikipedia.org
g8-tv.org
heise.de/tp
welt.de
jungewelt.de
spiegelfechter.com
sueddeutsche.de
ndr.de
tagesschau.de
youtube.com
spreeblick.com
politblog.net
netzeitung.de
stern.de
taz.de
stefan-niggemeier.de
polizei.mvnet.de
zeit.de
bild.t-online.de
g-8.de
zdf.de
heise.de
citronengras.de
faz.net
focus.de
freie-radios.net
gipfelsoli.org
Only nodes with indegree ≤ 2: 144 of 757 nodes, 233 of 1505 edges
node colour: red (activist sites, protest against g8), blue (external weblogs, main Internet portals), yellow (professional-edited news media), black (blogs
in the follow-up communication promoting links; non-classified sites).
16. The follow-up communication in blogs is mainly focused on selected
media items and articles
Contributions of Spiegel Online as well as Indymedia disparately provoked
follow-up communication in the blogosphere
Moderately connected clusters of blogs which bridge reactions to
Indymedia as well as Spiegel Online
Functional filtering based on a common and small selection of blog
postings which receive attention regarding a specific topic (center-periphery
pattern)
Most blog reactions remain isolated in the blogosphere. This indicates
that public follow-up communication does not necessarily switch into an
interactive mode of “networked conversation” (also few reciprocal ties)
The contributors‟ network leads to similarities regarding the distribution of
received comments (indicates filter-effectivity)
Topical patterns in the media are only partially reflected in the related
follow-up communication: blogs link more often to articles with criticism on the
media‟s conduct and highlight aspects which were less covered.
► Summary (RQ 1)
17. Most investigated blogs are published by independent single authors (77%,
n=239). Author collectives (16%) as well as blogs provided by political
organisations (4%) are less common [2010]
Low level of gender equality: 6% women„s share (n=96)
Low level of direct activism: 8% participated in a G8-protest rally
Signs of political partisanship: Positioning on a „left-right continuum” difficult
in most of the cases; leftists‟ share (20%, n=261)
„A-List“: 3% (n=323) belong to the German Top100 blogs
Visibility: 23% (n=261) don„t show any incoming links according to Google
Activity level: 35% (n=255) were updated at least five times in the last 30 days
[2010]
A minority of blogs exhibits signs for a journalistic affiliation of their author or
publisher (9%, n=258) [2010]
► Results (RQ 2)
Who participated? Characteristics of contributing bloggers
18. ► Outlook
Issue-specific filter mechanisms in participatory, network-based media demand
a comparative design
Identification of similar patterns regarding link formation, networking and
re-communication of content for examination of filter effectivity (homophily,
polarisation, centralisation)
Additional analysis of comments attached to blog postings
Study revealed that networking is rather not indicating endorsement
Future research should also focus on context of links
Further research is needed to examine the diffusion of news in network-based
media and specific processes of amplification in issue-related social networks
Considering external factors in the diffusion of social news
(Transparency regarding algorithms and code)
Temporal analysis: Filter dynamics
19. Thank you!
Dr. Christian Nuernbergk
Department of Communication Science
and Media Research (IfKW)
Ludwig-Maximilians-Universität München
nuernbergk@ifkw.lmu.de
twitter.com/nuernbergk
fb.com/pages/Lehrstuhl-Prof-Neuberger