Statistical Analysis of the Social Network and Discussion Threads in Slashdot
(0) We analyze the social network emerging from the user com-ment activity on the website Slashdot. The network presents common features of traditional social networks such as a gi-ant component, small average path length and high clustering, but di ers 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 distri-butions. We also study the structure of discussion threads using an intuitive radial tree representation. Threads show strong heterogeneity and self-similarity throughout the dif-ferent nesting levels of a conversation. We use these results to propose a simple measure to evaluate the degree of con-troversy provoked by a post.
social networks online communities bulletin board weblogs h-index log-normal power-law thread radial tree
Vicenc Gomez Andreas Kaltenbrunner Vicente Lopez
Barcelona Media Centre d’Innovació, Barcelona, Spain Dept. Tecnologia (DTIC), Universitat Pompeu Fabra, Barcelona, Spain
国际会议
第十七届国际万维网大会(the 17th International World Wide Web Conference)(WWW08)
北京
英文
2008-04-21（万方平台首次上网日期，不代表论文的发表时间）