Co-occurrence Analysis Focused on Blogger Communities

We studied the problem of finding a subspace of Web pages that is contextually consistent for co-occurrence analysis. We looked at blogs and proposed blogger-based co-occurrence analysis, which assumes that two items are relevant to each other if they appear in any of the blog entries posted by the same blogger. We show that (1) blogger-based analysis outperforms conventional page-based analysis in solving context-sensitive problems and that (2) analysis focused on bloggers forming a community yields better performance compared with that focused on isolated bloggers.

[1]  Stanley Wasserman,et al.  Social Network Analysis: Methods and Applications , 1994, Structural analysis in the social sciences.

[2]  Ramanathan V. Guha,et al.  Information diffusion through blogspace , 2004, WWW '04.

[3]  Kôiti Hasida,et al.  POLYPHONET: An advanced social network extraction system from the Web , 2007, J. Web Semant..

[4]  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.

[5]  Ravi Kumar,et al.  On the Bursty Evolution of Blogspace , 2003, WWW '03.

[6]  Nancy Ide,et al.  Introduction to the Special Issue on Word Sense Disambiguation: The State of the Art , 1998, Comput. Linguistics.

[7]  Bart Selman,et al.  The Hidden Web , 1997, AI Mag..

[8]  Jaideep Srivastava,et al.  Selecting the right interestingness measure for association patterns , 2002, KDD.