Visually Exploring Social Participation in Encyclopedia of Life

Social network visualization is useful for understanding the complex structure of collaborative efforts such as citizen science projects. It has been widely accepted by social network analysts for exploring and analyzing networks by visually showing their members, the relationships among them, and their behaviors and attributes. The strength of social network visualization can be increased even further, by incorporating the time dimension of evolving networks. We analyzed the conversation network of a collaborative citizen science web platform called the Encyclopedia of Life using dynamic network visualization methods. This paper shows how the temporal visualization was applied to the social collaboration analysis of EOL and presents the findings. We found that some EOL web site features increased the interactive as well as individual member activities. We also found evidence that EOL curator activities encouraged the activities of other members.

[1]  Daniel A. McFarland,et al.  Dynamic Network Visualization1 , 2005, American Journal of Sociology.

[2]  Ben Shneiderman,et al.  A Task Taxonomy for Network Evolution Analysis , 2014, IEEE Transactions on Visualization and Computer Graphics.

[3]  Lisa Singh,et al.  Visual analysis of dynamic group membership in temporal social networks , 2007, SKDD.

[4]  G. Miller.  Sociology. Social scientists wade into the tweet stream. , 2011, Science.

[5]  Fernanda B. Viégas,et al.  Newsgroup Crowds and AuthorLines: visualizing the activity of individuals in conversational cyberspaces , 2004, 37th Annual Hawaii International Conference on System Sciences, 2004. Proceedings of the.

[6]  Edward M. Reingold,et al.  Graph drawing by force‐directed placement , 1991, Softw. Pract. Exp..

[7]  Kevin Crowston,et al.  From Conservation to Crowdsourcing: A Typology of Citizen Science , 2011, 2011 44th Hawaii International Conference on System Sciences.

[8]  Lyndon Kennedy,et al.  In the Limelight Over Time: Temporalities of Network Centrality , 2011 .

[9]  Yan Zhao,et al.  Analyzing Actors and Their Discussion Topics by Semantic Social Network Analysis , 2006, Tenth International Conference on Information Visualisation (IV'06).

[10]  Niklas Elmqvist,et al.  TimeMatrix: Analyzing Temporal Social Networks Using Interactive Matrix-Based Visualizations , 2010, Int. J. Hum. Comput. Interact..

[11]  Gary D Bader,et al.  Systematic identification of protein complexes in Saccharomyces cerevisiae by mass spectrometry , 2002, Nature.

[12]  Martina Morris,et al.  Concurrent partnerships and HIV prevalence disparities by race: linking science and public health practice. , 2009, American journal of public health.

[13]  Paul Mutton,et al.  Inferring and visualizing social networks on Internet relay chat , 2004, Proceedings. Eighth International Conference on Information Visualisation, 2004. IV 2004..

[14]  Chris North,et al.  An Evaluation of Microarray Visualization Tools for Biological Insight , 2004 .

[15]  Abdulmonem Alabri,et al.  Enhancing the Quality and Trust of Citizen Science Data , 2010, 2010 IEEE Sixth International Conference on e-Science.

[16]  B. Shneiderman,et al.  The Reader-to-Leader Framework: Motivating Technology-Mediated Social Participation , 2009 .

[17]  Ben Shneiderman,et al.  Social discovery in an information abundant world: Designing to create capacity and seek solutions , 2011, Inf. Serv. Use.

[18]  Aniket Kittur,et al.  Lifting the veil: improving accountability and social transparency in Wikipedia with wikidashboard , 2008, CHI.

[19]  Brian L. Sullivan,et al.  eBird: A citizen-based bird observation network in the biological sciences , 2009 .

[20]  Ben Shneiderman,et al.  Temporal Visualization of Social Network Dynamics: Prototypes for Nation of Neighbors , 2011, SBP.

[21]  Aniket Kittur,et al.  He says, she says: conflict and coordination in Wikipedia , 2007, CHI.

[22]  Jacob L. Moreno,et al.  Who shall survive? : foundations of sociometry, group psychotherapy, and sociodrama , 1953 .

[23]  Philippe A. Palanque,et al.  Proceedings of the SIGCHI Conference on Human Factors in Computing Systems , 2014, International Conference on Human Factors in Computing Systems.

[24]  Daniel A. McFarland,et al.  The Art and Science of Dynamic Network Visualization , 2006, J. Soc. Struct..

[25]  W. Powell,et al.  Network Dynamics and Field Evolution: The Growth of Interorganizational Collaboration in the Life Sciences1 , 2005, American Journal of Sociology.

[26]  Xi Chen,et al.  Visual Analysis of Temporal Trends in Social Networks Using Edge Color Coding and Metric Timelines , 2011, 2011 IEEE Third International Conference on Privacy, Security, Risk and Trust and 2011 IEEE Third International Conference on Social Computing.

[27]  Jean-Daniel Fekete,et al.  MatrixExplorer: a Dual-Representation System to Explore Social Networks , 2006, IEEE Transactions on Visualization and Computer Graphics.

[28]  Jennifer Preece,et al.  Dynamic changes in motivation in collaborative citizen-science projects , 2012, CSCW.

[29]  Kevin Crowston,et al.  Validity Issues in the Use of Social Network Analysis with Digital Trace Data , 2011, J. Assoc. Inf. Syst..

[30]  Jennifer Preece,et al.  Supporting content curation communities: The case of the Encyclopedia of Life , 2012, J. Assoc. Inf. Sci. Technol..

[31]  N. Christakis,et al.  The Spread of Obesity in a Large Social Network Over 32 Years , 2007, The New England journal of medicine.

[32]  Shalin Hai-Jew.  Analyzing Social Media Networks with NodeXL: Insights from a Connected World , 2012 .

[33]  Elisha Peterson.  Time spring layout for visualization of dynamic social networks , 2011, 2011 IEEE Network Science Workshop.

[34]  Judith S. Olson,et al.  From Shared Databases to Communities of Practice: A Taxonomy of Collaboratories , 2007, J. Comput. Mediat. Commun..

[35]  David A. Shamma,et al.  Peaks and persistence: modeling the shape of microblog conversations , 2011, CSCW '11.