Leveraging Collective Intelligence through Community Detection in Tag Networks ∗

The paper studies the problem of community detection in tag networks, i.e. networks consisting of associations between tags that are used within Social Tagging Systems (STS) to annotate online resources (e.g. bookmarks, pictures, videos, etc.). Community detection methods aim at uncovering densely connected groups of tags, which can reveal the topic structure emerging in the STS. In this way, community detection in tag networks leverages Collective Intelligence (CI), that is the intelligence that is accumulated as a result of the collective activities of masses of users.

[1]  Timothy W. Finin,et al.  Detecting Commmunities via Simultaneous Clustering of Graphs and Folksonomies , 2008, WebKDD 2008.

[2]  M E J Newman,et al.  Community structure in social and biological networks , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[3]  Yiannis Kompatsiaris,et al.  Bridge Bounding: A Local Approach for Efficient Community Discovery in Complex Networks , 2009, 0902.0871.

[4]  Vittorio Loreto,et al.  Emergent Community Structure in Social Tagging Systems , 2008, Adv. Complex Syst..

[5]  Claudio Castellano,et al.  Community Structure in Graphs , 2007, Encyclopedia of Complexity and Systems Science.

[6]  J. Doye,et al.  Identifying communities within energy landscapes. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[7]  Edwin Simpson,et al.  Clustering Tags in Enterprise and Web Folksonomies , 2021, ICWSM.

[8]  A. Clauset.  Finding local community structure in networks. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[9]  Jean-Marc Petit,et al.  Web Intelligence and Intelligent Agent Technology , 2011 .

[10]  Christopher H. Brooks,et al.  Improved annotation of the blogosphere via autotagging and hierarchical clustering , 2006, WWW '06.

[11]  Bernardo A. Huberman,et al.  Usage patterns of collaborative tagging systems , 2006, J. Inf. Sci..

[12]  S. Fortunato,et al.  Resolution limit in community detection , 2006, Proceedings of the National Academy of Sciences.

[13]  M E J Newman,et al.  Finding and evaluating community structure in networks. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[14]  Toby Segaran,et al.  Programming Collective Intelligence , 2007 .

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

[16]  Xiaowei Xu,et al.  SCAN: a structural clustering algorithm for networks , 2007, KDD '07.

[17]  Feng Luo,et al.  Exploring Local Community Structures in Large Networks , 2006, 2006 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2006 Main Conference Proceedings)(WI'06).

[18]  Y. Benkler,et al.  Collective Intelligence: Creating a Prosperous World at Peace , 2008 .

[19]  M. Newman,et al.  Finding community structure in networks using the eigenvectors of matrices. , 2006, Physical review. E, Statistical, nonlinear, and soft matter physics.

[20]  James P. Bagrow.  Evaluating local community methods in networks , 2007, 0706.3880.

[21]  Satnam Alag,et al.  Collective Intelligence in Action , 2008 .

[22]  T. Vicsek,et al.  Uncovering the overlapping community structure of complex networks in nature and society , 2005, Nature.

[23]  Bamshad Mobasher,et al.  Personalizing Navigation in Folksonomies Using Hierarchical Tag Clustering , 2008, DaWaK.

[24]  Valentin Robu,et al.  The complex dynamics of collaborative tagging , 2007, WWW '07.

[25]  M. Newman,et al.  Finding community structure in very large networks. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[26]  Ciro Cattuto,et al.  Semantic Analysis of Tag Similarity Measures in Collaborative Tagging Systems , 2008, LWA.

[27]  Andreas Hotho,et al.  Emergent Semantics in BibSonomy , 2006, GI Jahrestagung.

[28]  Bin Wu,et al.  Overlapping Community Detection in Bipartite Networks , 2008, 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology.

[29]  M E J Newman,et al.  Fast algorithm for detecting community structure in networks. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[30]  A. Arenas,et al.  Community detection in complex networks using extremal optimization. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.