Statistical analysis of the social network and discussion threads in slashdot

  • Authors:
  • Vicenç Gómez;Andreas Kaltenbrunner;Vicente López

  • Affiliations:
  • Universitat Pompeu Fabra, Barcelona, Spain;Universitat Pompeu Fabra, Barcelona, Spain;Barcelona Media Centre d'Innovació, Barcelona, Spain

  • Venue:
  • Proceedings of the 17th international conference on World Wide Web
  • Year:
  • 2008

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Abstract

We analyze the social network emerging from the user comment activity on the website Slashdot. The network presents common features of traditional social networks such as a giant component, small average path length and high clustering, but differs from them showing moderate reciprocity and neutral assortativity by degree. Using Kolmogorov-Smirnov statistical tests, we show that the degree distributions are better explained by log-normal instead of power-law distributions. We also study the structure of discussion threads using an intuitive radial tree representation. Threads show strong heterogeneity and self-similarity throughout the different nesting levels of a conversation. We use these results to propose a simple measure to evaluate the degree of controversy provoked by a post.