Implicit Structure and the Dynamics of Blogspace

Weblogs link together in a complex structure through which new ideas and discourse can flow. Such a structure is ideal for the study of the propagation of information. In this paper we describe general categories of information epidemics and create a tool to infer and visualize the paths specific infections take through the network. This inference is based in part on a novel utilization of data describing historical, repeating patterns of infection. We conclude with a description of a new ranking algorithm, iRank, for blogs. In contrast to traditional ranking strategies, iRank acts on the implicit link structure to find those blogs that initiate these epidemics. General Terms Measurement, Experimentation, Algorithm

[1]  Ben Taskar,et al.  Link Prediction in Relational Data , 2003, NIPS.

[2]  John Skvoretz,et al.  Advances in biased net theory: definitions, derivations, and estimations , 2004, Soc. Networks.

[3]  David S. Munro,et al.  In: Software-Practice and Experience , 2000 .

[4]  Emden R. Gansner,et al.  An open graph visualization system and its applications to software engineering , 2000 .

[5]  L. Matthews,et al.  The construction and analysis of epidemic trees with reference to the 2001 UK foot–and–mouth outbreak , 2003, Proceedings of the Royal Society of London. Series B: Biological Sciences.

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

[7]  Rajeev Motwani,et al.  The PageRank Citation Ranking : Bringing Order to the Web , 1999, WWW 1999.

[8]  R. Lewontin.  ‘The Selfish Gene’ , 1977, Nature.

[9]  Lada A. Adamic,et al.  Tracking information epidemics in blogspace , 2005, The 2005 IEEE/WIC/ACM International Conference on Web Intelligence (WI'05).

[10]  S. Chick,et al.  Methods and measures for the description of epidemiologic contact networks , 2001, Journal of urban health.

[11]  Jon Kleinberg,et al.  The link prediction problem for social networks , 2003, CIKM '03.

[12]  Emden R. Gansner,et al.  An open graph visualization system and its applications to software engineering , 2000, Softw. Pract. Exp..

[13]  Hinrich Schütze,et al.  Book Reviews: Foundations of Statistical Natural Language Processing , 1999, CL.

[14]  Carter T. Butts,et al.  Network inference, error, and informant (in)accuracy: a Bayesian approach , 2003, Soc. Networks.