Extraction and analysis of tripartite relationships from Wikipedia

Social aspects are critical in the decision making process for social actors (human beings). Social aspects can be categorized into social interaction, social communities, social groups or any kind of behavior that emerges from interlinking, overlapping or similarities between interests of a society. These social aspects are dynamic and emergent. Therefore, interlinking them in a social structure, based on bipartite affiliation network, may result in isolated graphs. The major reason is that as these correspondences are dynamic and emergent, they should be coupled with more than a single affiliation in order to sustain the interconnections during interest evolutions. In this paper we propose to interlink actors using multiple tripartite graphs rather than a bipartite graph which was the focus of most of the previous social network building techniques. The utmost benefit of using tripartite graphs is that we can have multiple and hierarchical links between social actors. Therefore in this paper we discuss the extraction, plotting and analysis methods of tripartite relations between authors, articles and categories from Wikipedia. Furthermore, we also discuss the advantages of tripartite relationships over bipartite relationships. As a conclusion of this study we argue based on our results that to build useful, robust and dynamic social networks, actors should be interlinked in one or more tripartite networks.

[1]  Bettina Berendt,et al.  Ubiquitous Social Networks: Opportunities and Challenges for Privacy-Aware User Modelling , 2007 .

[2]  Ravi Kumar,et al.  Trawling the Web for Emerging Cyber-Communities , 1999, Comput. Networks.

[3]  Lada A. Adamic,et al.  A social network caught in the Web , 2003, First Monday.

[4]  Gianluca Demartini,et al.  Finding Experts Using Wikipedia , 2007, FEWS.

[5]  M. Newman Properties of highly clustered networks. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[6]  Peter Mika Ontologies Are Us: A Unified Model of Social Networks and Semantics , 2005, International Semantic Web Conference.

[7]  Malcolm Laurence Alexander Using the bipartite line graph to visualise 2-mode social networks , 2005 .

[8]  H. Park Hyperlink network analysis: A new method for the study of social structure on the web , 2003 .

[9]  M. Newman 1 Who is the best connected scientist ? A study of scientific coauthorship networks , 2004 .

[10]  Amit P. Sheth,et al.  Semantic analytics on social networks: experiences in addressing the problem of conflict of interest detection , 2006, WWW '06.

[11]  Mark S. Ackerman,et al.  Expertise networks in online communities: structure and algorithms , 2007, WWW '07.

[12]  M. Newman Analysis of weighted networks. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[13]  Caroline Haythornthwaite,et al.  Studying Online Social Networks , 2006, J. Comput. Mediat. Commun..