The Journal of Machine Learning Research
Statistical analysis of the social network and discussion threads in slashdot
Proceedings of the 17th international conference on World Wide Web
Harnessing the wisdom of crowds in wikipedia: quality through coordination
Proceedings of the 2008 ACM conference on Computer supported cooperative work
Meme-tracking and the dynamics of the news cycle
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
The nested chinese restaurant process and bayesian nonparametric inference of topic hierarchies
Journal of the ACM (JACM)
Finding social roles in Wikipedia
Proceedings of the 2011 iConference
Understanding and improving Wikipedia article discussion spaces
Proceedings of the 2011 ACM Symposium on Applied Computing
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Social news and content aggregation Web sites have become massive repositories of valuable knowledge on a diverse range of topics. Millions of Web-users are able to leverage these platforms to submit, view and discuss nearly anything. The users themselves exclusively curate the content with an intricate system of submissions, voting and discussion. Furthermore, the data on social news Web sites is extremely well organized by its user-base, which opens the door for opportunities to leverage this data for other purposes just like Wikipedia data has been used for many other purposes. In this paper we study a popular social news Web site called Reddit. Our investigation looks at the dynamics of its discussion threads, and asks two main questions: (1) to what extent do discussion threads resemble a topical hierarchy? and (2) Can discussion threads be used to enhance Web search? We show interesting results for these questions on a very large snapshot several sub-communities of the Reddit Web site. Finally, we discuss the implications of these results and suggest ways by which social news Web site's can be used to perform other tasks.