Sensing trending topics in twitter

IEEE Transactions on Multimedia

Volumn 15, Issue 6, 2013, Pages 1268-1282

  Aiello, Luca Maria ^a   Petkos, Georgios ^b   Martin, Carlos ^c   Corney, David ^c   Papadopoulos, Symeon ^b   Skraba, Ryan ^d   Goker, Ayse ^e   Kompatsiaris, Ioannis ^b   Jaimes, Alejandro ^a  

^a YAHOO RESEARCH   (Spain)

^b INFORMATION TECHNOLOGIES INSTITUTE   (Greece)

^c CITY UNIVERSITY   (United Kingdom)

^d LUCENT TECHNOLOGIES   (United States)

^e ROBERT GORDON UNIVERSITY   (United Kingdom)

Author keywords

Information filtering; social media; social sensing; text mining; topic detection; Twitter

Indexed keywords

SOCIAL MEDIA; SOCIAL SENSING; TEXT MINING; TOPIC DETECTION; TWITTER;

DATA MINING; INFORMATION FILTERING; NATURAL LANGUAGE PROCESSING SYSTEMS;

SOCIAL NETWORKING (ONLINE);

EID: 84884554344     PISSN: 15209210     EISSN: None     Source Type: Journal    
DOI: 10.1109/TMM.2013.2265080     Document Type: Article

References (45)

1. A. Panisson, Visualization of Egyptian Revolution on Twitter, Feb. 2011. [Online]. Available: http://slashdot.org/story/11/02/15/1544254.
2. M.Wall and S. E. L. Zahed, ""I'll be waiting for you guys": A YouTube call to action in the Egyptian revolution," J. Commun., vol. 5, pp. 1333-1343, 2011.
3. T. Sakaki, M. Okazaki, and Y. Matsuo, "Earthquake shakes twitter users: Real-time event detection by social sensors," in Proc. WWW: 19th ACM Int. Conf. World Wide Web., 2010, pp. 851-860, ACM.
4. M. D. Conover, B. Gonçalves, J. Ratkiewicz, A. Flammini, and F. Menczer, "Predicting the political alignment of twitter users," in Proc. SocialCom: 3rd IEEE Int. Conf. Social Computing, Boston, MA, USA, Oct. 2011.
5. R. Kumar, J. Novak, and A. Tomkins, "Structure and evolution of online social networks," in Proc. KDD: 12th ACM Int. Conf. Knowledge Discovery and Data Mining, New York, NY, USA, 2006, pp. 611-617. (Pubitemid 44535563)
6. J. Leskovec, L. Backstrom, R. Kumar, and A. Tomkins, "Microscopic evolution of social networks," in Proc. KDD: 14th ACM Int. Conf. Knowledge Discovery and Data Mining, New York, NY, USA, 2008, pp. 462-470.
7. M. Cha, A. Mislove, and K. P. Gummadi, "A measurement-driven analysis of information propagation in the Flickr social network," in Proc. WWW: 18th ACM Int. Conf. World Wide Web., New York, NY, USA, 2009, pp. 721-730.
8. L. M. Aiello, A. Barrat, R. Schifanella, C. Cattuto, B. Markines, and F. Menczer, "Friendship prediction and homophily in social media," ACM Trans. Web, vol. 6, no. 2, pp. 9:1-9:33, Jun. 2012.
9. S. Papadopoulos, A. Vakali, and I. Kompatsiaris, "The dynamics of content popularity in social media," Int. J. Data Warehous. Min., vol. 6, no. 1, pp. 20-37, 2010.
10. S. Cohen, J. T. Hamilton, and F. Turner, "Computational journalism," Commun. ACM, vol. 54, pp. 66-71, Oct. 2011.
11. New York Times Cascade Project-nytlabs.com/projects/cascade. html, 2011.
12. D. Quercia, J. Ellis, L. Capra, and J. Crowcroft, "Tracking "Gross community happiness" from tweets," in Proc. CSCW: ACM Conf. Computer Supported Cooperative Work, New York, NY, USA, 2012, pp. 965-968.
13. J. Ratkiewicz, M. Conover, M. Meiss, B. Gonçalves, A. Flammini, and F. Menczer, "Detecting and tracking political abuse in social media," in Proc. ICSWM: 5th Int. AAAI Conf. Weblogs and Social Media, 2011.
14. Y. Boshmaf, I. Muslukhov, K. Beznosov, and M. Ripeanu, "The socialbot network: When bots socialize for fame and money," in Proc. ACSAC: 27th Annual Computer Security Applications Conf., New York, NY, USA, 2011, pp. 93-102, ACM.
15. L. M. Aiello, M. Deplano, R. Schifanella, and G. Ruffo, "People are strange when you're a stranger: Impact and influence of bots on social networks," in Proc. ICWSM: 6th AAAI Int. Conf. Weblogs and Social Media. AAAI, 2012, pp. 10-17.
16. , J. Allan, Ed., Topic Detection and Tracking: Event-Based Information Qrganization. Norwell, MA, USA: Kluwer, 2002.
17. S. Phuvipadawat and T.Murata, "Breaking news detection and tracking in Twitter," in Proc.Web Intelligence and Intelligent Agent Technology, IEEE/WIC/ACM Int. Conf., 2010, vol. 3, pp. 120-123.
18. B. O'Connor, M. Krieger, and D. Ahn, "TweetMotif: Exploratory search and topic summarization for Twitter," in ICWSM, W. W. Cohen, S. Gosling, W. W. Cohen, and S. Gosling, Eds. Palo Alto, CA, USA: AAAI Press, 2010.
19. H. Becker, M. Naaman, and L. Gravano, "Beyond trending topics: Real-world event identification on Twitter," in Proc. ICWSM: 5th Int. AAAI Conf. Weblogs and Social Media, 2011.
20. J. Sankaranarayanan, H. Samet, B. E. Teitler, M. D. Lieberman, and J. Sperling, "Twitter stand: News in tweets," in Proc. GIS: 17th ACM Int. Conf. Advances in Geographic Information Systems, New York, NY, USA, 2009, pp. 42-51.
21. G. P. C. Fung, J. X. Yu, P. S. Yu, and H. Lu, "Parameter free bursty events detection in text streams," in Proc. VLDB: 31st Int. Conf. Very Large Data Bases, 2005, pp. 181-192, VLDB Endowment. (Pubitemid 43991003)
22. S. Petrovi?, M. Osborne, and V. Lavrenko, "Streaming first story detection with application to Twitter," in Proc. HLT: Annual Conf. North American Chapter of the Association for Computational Linguistics, Stroudsburg, PA, USA, 2010, pp. 181-189.
23. D. M. Blei, A. Y. Ng, and M. I. Jordan, "Latent dirichlet allocation," J. Mach. Learn. Res., vol. 3, pp. 993-1022, Mar. 2003.
24. D.M. Blei and J. D. Lafferty, "Dynamic topic models," in Proc. ICML: 23rd Int. Conf. Machine Learning, New York, NY, USA, 2006, pp. 113-120, ACM.
25. D. A. Shamma, L. Kennedy, and E. F. Churchill, "Peaks and persistence: Modeling the shape of microblog conversations," in Proc. CSCW: ACM Conf. Computer Supported Cooperative Work, New York, NY, USA, 2011, pp. 355-358.
26. J. Yang and J. Leskovec, "Patterns of temporal variation in online media," in Proc. WSDM: 4th ACM Int. Conf. Web Search and Data Mining, New York, NY, USA, 2011, pp. 177-186.
27. J. Lehmann, B. Gonçalves, J. J. Ramasco, and C. Cattuto, "Dynamical classes of collective attention in Twitter," in Proc. WWW: 21st ACM Int. Conf. World Wide Web, New York, NY, USA, 2012, pp. 251-260.
28. M. Mathioudakis and N. Koudas, "Twitter monitor: Trend detection over the Twitter stream," in Proc. SIGMOD: Int. Conf. Management of Data, New York, NY, USA, 2010, pp. 1155-1158, ACM.
29. H. Sayyadi, M. Hurst, and A.Maykov, "Event detection and tracking in social streams," in ICWSM, E. Adar, M. Hurst, T. Finin, N. S. Glance, N. Nicolov, and B. L. Tseng, Eds. Palo Alto, CA, USA: AAAI Press, 2009.
30. J. Leskovec, L. Backstrom, and J. Kleinberg, "Meme-tracking and the dynamics of the news cycle," in Proc. KDD: 15th ACM Int. Conf. Knowledge Discovery and Data Mining, New York, NY, USA, 2009, pp. 497-506.
31. S. Papadopoulos, Y. Kompatsiaris, and A. Vakali, "A graph-based clustering scheme for identifying related tags in folksonomies," in Proc. DaWaK: 12th Int. Conf. Data Warehousing and Knowledge Discovery. Berlin, Germany: Springer-Verlag, 2010, pp. 65-76.
32. J. Weng and B.-S. Lee, "Event detection in Twitter," in Proc. 5th Int. Conf. Weblogs and Social Media. Palo Alto, CA, USA: AAAI Press, 2011.
33. Q. He, K. Chang, and E.-P. Lim, "Analyzing feature trajectories for event detection," in Proc. SIGIR: 30th Annual Int. ACMConf. Research and Development in Information Retrieval,NewYork,NY, USA, 2007, pp. 207-214. (Pubitemid 350164963)
34. M. Cataldi, L. Di Caro, and C. Schifanella, "Emerging topic detection on Twitter based on temporal and social terms evaluation," in Proc. MDMKDD: 10th Int. Workshop Multimedia Data Mining, New York, NY, USA, 2010, pp. 4:1-4:10, ACM.
35. S. Diplaris, G. Petkos, S. Papadopoulos, Y. Kompatsiaris, N. Sarris, C. Martin, A. Göker, D. Corney, J. Geurts, Y. Liu, and J.-C. Point, "Social sensor: Surfacing real-time trends and insights from multiple social networks," in Proc. 2012 NEM Summit, Oct. 2012, pp. 47-52.
36. M. F. Porter, "An algorithm for suffix stripping," in Readings in Information Retrieval, K. Sparck Jones and P.Willett, Eds. San Francisco, CA, USA: Morgan Kaufmann, 1997, pp. 313-316.
37. Y. W. Teh, D. Newman, and M. Welling, "A collapsed variational Bayesian inference algorithm for latent Dirichlet allocation," in Adv. Neural Inf. Process. Syst., 2007, vol. 19.
38. Y. W. Teh, M. I. Jordan, M. J. Beal, and D. M. Blei, "Hierarchical Dirichlet processes," J. Amer. Statist. Assoc., vol. 101, no. 476, pp. 1566-1581, 2006.
39. G. Salton and M. J. McGill, Introduction to Modern Information Retrieval. New York, NY, USA: McGraw-Hill, 1986.
40. X.Xu, N. Yuruk, Z. Feng, and T. A. J. Schweiger, "SCAN: A structural clustering algorithmfor networks," in Proc. KDD: 13th ACM Int. Conf. Knowledge Discovery and Data Mining, New York, NY, USA, 2007, pp. 824-833. (Pubitemid 350237348)
41. B. Goethals, Frequent Set Mining, 2005, pp. 377-397.
42. C.Gy?rödi andR. Gy?rödi, AComparative Study ofAssociation Rules Mining Algorithms, 2004.
43. H. Li, Y. Wang, D. Zhang, M. Zhang, and E. Y. Chang, "PFP: Parallel FP-growth for query recommendation," in Proc. RecSys: ACM Conf. Recommender Systems, New York, NY, USA, 2008, pp. 107-114.
44. J. R. Finkel, T. Grenager, and C. Manning, "Incorporating non-local information into information extraction systems by Gibbs sampling," in Proc. ACL: 43rd Annual Meeting on Association for Computational Linguistics, Stroudsburg, PA, USA, 2005, pp. 363-370.
45. F. Murtagh, "A survey of recent advances in hierarchical clustering algorithms," Comput. J., vol. 26, no. 4, pp. 354-359, 1983. (Pubitemid 14590891)