document: Statistical analysis of the social network and discussion threads in slashdot 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 .
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