Ranking twitter discussion groups

COSN 2014 - Proceedings of the 2014 ACM Conference on Online Social Networks

Volumn , Issue , 2014, Pages 177-189

  Cook, James ^a   Das, Abhimanyu ^b   Kenthapadi, Krishnaram ^b   Mishra, Nina ^b  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b MICROSOFT RESEARCH   (United States)

Author keywords

Discussion groups; Group chats; Group preference; Group search; Online communities; Ranking groups; Twitter groups

Indexed keywords

RANDOM PROCESSES; SOCIAL NETWORKING (ONLINE);

DISCUSSION GROUPS; GROUP CHATS; GROUP PREFERENCE; GROUP SEARCH; ON-LINE COMMUNITIES; RANKING GROUPS; TWITTER GROUPS;

LEARNING TO RANK;

EID: 84912058101     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2660460.2660473     Document Type: Conference Paper

References (52)

1. R. Agrawal, A. Halverson, K. Kenthapadi, N. Mishra, and P. Tsaparas. Generating labels from clicks. In WSDM, 2009.
2. L. Backstrom, D. Huttenlocher, J. Kleinberg, and X. Lan. Group formation In large social networks: Membership, growth, and evolution. In KDD, 2006.
3. L. Backstrom, R. Kumar, C. Marlow, J. Novak, and A. Tomkins. Preferential behavior In online groups. In WSDM, 2008.
4. S. Brin and L. Page. The anatomy of a large-scale hypertextual Web search engine. Computer Networks and ISDN Systems, 30, 1998.
5. C. Budak and R. Agrawal. Participation In group chats on Twitter. In WWW, 2013.
6. C. Burges, R. Ragno, and Q. V. Le. Learning to rank with nonsmooth cost functions. In NIPS, 2006.
7. C. Burges, T. Shaked, E. Renshaw, A. Lazier, M. Deeds, N. Hamilton, and G. Hullender. Learning to rank using gradient descent. In ICML, 2005.
8. B. S. Butler. Membership size, communication activity, and sustainability: A resource-based model of online social structures. Info. Sys. Research, 12(4), Dec. 2001.
9. R. Chaiken, B. Jenkins, P. Larson, B. Ramsey, D. Shakib, S. Weaver, and J. Zhou. SCOPE: Easy and efficient parallel processing of massive data sets. PVLDB, 1(2), 2008.
10. S. Chien, C. Dwork, R. Kumar, D. R. Simon, and D. Sivakumar. Link evolution: Analysis and algorithms. Internet Mathematics, 1(3), 2003.
11. W. Cohen, R. Schapire, and Y. Singer. Learning to order things. JAIR, 10, 1999.
12. G. Cong, L. Wang, C.-Y. Lin, Y.-I. Song, and Y. Sun. Finding question-answer pairs from online forums. In SIGIR, 2008.
13. J. Cook, K. Kenthapadi, and N. Mishra. Group chats on Twitter. In WWW, 2013.
14. K. Csalogány, D. Fogaras, B. Rácz, and T. Sarl'os. Towards scaling fully personalized pagerank: Algorithms, lower bounds, and experiments, 2005.
15. C. Danescu-Niculescu-Mizil, R. West, D. Jurafsky, J. Leskovec, and C. Potts. No country for old members: User lifecycle and linguistic change In online communities. In WWW, 2013.
16. K. Ehrlich, C.-Y. Lin, and V. Griffiths-Fisher. Searching for experts In the enterprise: Combining text and social network analysis. In GROUP, 2007.
17. J. L. Elsas and J. G. Carbonell. It pays to be picky: An evaluation of thread retrieval In online forums. In SIGIR, 2009.
18. D. Forsyth. Group dynamics. Wadsworth, 2009.
19. S. Ghosh, N. K. Sharma, F. Benevenuto, N. Ganguly, and P. K. Gummadi. Cognos: Crowdsourcing search for topic experts In microblogs. In SIGIR, 2012.
20. F. Godin, V. Slavkovikj, W. D. Neve, B. Schrauwen, and R. V. de Walle. Using topic models for Twitter hashtag recommendation. In www (Companion Volume), 2013.
21. P. Gupta, A. Goel, J. Lin, A. Sharma, D. Wang, and R. Zadeh. WTF: The who to follow service at Twitter. In WWW, 2013.
22. W. Hartzog and F. Stutzman. The case for online obscurity. California Law Review, 101(1), 2013.
23. S. Ieong, N. Mishra, and O. Sheffet. Predicting preference flips In commerce search. In ICML, 2012.
24. A. Iriberri and G. Leroy. A life-cycle perspective on online community success. CSUR, 41(2), 2009.
25. G. Jeh and J. Widom. Scaling personalized web search. In WWW, 2003.
26. J. Jiao, J. Yan, H. Zhao, and W. Fan. Expertrank: An expert user ranking algorithm In online communities. In NISS, 2009.
27. T. Joachims. Optimizing search engines using clickthrough data. In KDD, 2002.
28. T. Joachims, L. Granka, B. Pan, H. Hembrooke, F. Radlinski, and G. Gay. Evaluating the accuracy of implicit feedback from clicks and query reformulations In web search. ACM Trans. Inf. Syst, 25(2), 2007.
29. Q. Jones, G. Ravid, and S. Rafaeli. Information overload and the message dynamics of online Interaction spaces: A theoretical model and empirical exploration. Info. Sys. Research, 15(2), 2004.
30. E. Joyce and R. Kraut. Predicting continued participation In newsgroups. J. Comput. Mediat. Comm, 11(3), 2006.
31. H. Kautz, B. Selman, and M. Shah. Referral web: Combining social networks and collaborative filtering. Commun. ACM, 40(3), 1997.
32. J. Kleinberg. Authoritative sources In a hyperlinked environment. In SODA, 1998.
33. G. Kossinets and D. J. Watts. Empirical analysis of an evolving social network. Science, 311(5757), 2006.
34. S. M. Kywe, T. A. Hoang, E. P. Lim, and F. Zhu. On recommending hashtags In Twitter networks. In SocInfo, 2012.
35. C. Lampe and E. Johnston. Follow the (slash) dot: Effects of feedback on new members In an online community. In GROUP, 2005.
36. R. Lempel and S. Moran. Salsa: The stochastic approach for link-structure analysis. ACM TOIS, 19(2), 2001.
37. R. Lempel and S. Moran. Rank-stability and rank-similarity of link-based web ranking algorithms In authority-connected graphs. Information Retrieval, 8(2), 2005.
38. M. L. Markus. Toward a "critical mass" theory of Interactive media universal access, Interdependence and diffusion. Communication research, 14(5), 1987.
39. M. Najork, S. Gollapudi, and R. Panigrahy. Less is more: Sampling the neighborhood graph makes SALSA better and faster. In WSDM, 2009.
40. L. Page, S. Brin, R. Motwani, and T. Winograd. The PageRank citation ranking: Bringing order to the web. Technical report, Stanford InfoLab, 1999.
41. A. Pal and S. Counts. Identifying topical authorities In microblogs. In WSDM, 2011.
42. A. Rajaraman and J. D. Ullman. Mining of massive datasets. Cambridge University Press, 2011.
43. T. Reichling, K. Schubert, and V. Wulf. Matching human actors based on their texts: Design and evaluation of an Instance of the expertfinding framework. In GROUP, 2005.
44. Y. Ren and R. E. Kraut. A simulation for designing online community: Member motivation, contribution, and discussion moderation. Info. Sys. Research, 2011.
45. B. Saha and L. Getoor. Group proximity measure for recommending groups In online social networks. In SNA-KDD Workshop, 2008.
46. T. Sakai. On the reliability of Information retrieval metrics based on graded relevance. Inform. Process. Manag, 2007.
47. P. Tsaparas. Using non-linear dynamical systems for web searching and ranking. In PODS, 2004.
48. A. Tversky. Elimination by aspects: A theory of choice. Psychological review, 79(4), 1972.
49. E. M. Voorhees and D. K. Harman. TREC: Experiment and evaluation In Information retrieval. MIT Press, 2005.
50. S. Whittaker, L. Terveen, W. Hill, and L. Cherny. The dynamics of mass Interaction. In From Usenet to CoWebs. Springer London, 2003.
51. L. Yang, T. Sun, M. Zhang, and Q. Mei. We know what @you #tag: Does the dual role affect hashtag adoption? In WWW, 2012.
52. E. Zangerle and W. Gassler. Recommending #-tags In Twitter. In CEUR Workshop, 2011.