Twitter: Who gets caught? Observed trends in social micro-blogging spam

WebSci 2014 - Proceedings of the 2014 ACM Web Science Conference

Volumn , Issue , 2014, Pages 33-41

  Almaatouq, Abdullah ^a   Alabdulkareem, Ahmad ^a   Nouh, Mariam ^a   Shmueli, Erez ^b   Alsaleh, Mansour ^c   Singh, Vivek K ^b  

^a Center for Complex Engineering Systems KACST and MIT   (United States)

^b MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^c KING ABDULAZIZ CITY FOR SCIENCE AND TECHNOLOGY   (Saudi Arabia)

Author keywords

Account abuse; Microblogging; Online social networks; Spam

Indexed keywords

SOCIAL NETWORKING (ONLINE); SOCIAL SCIENCES; SPAMMING;

ACCOUNT ABUSE; BEHAVIORAL CHARACTERISTICS; MICROBLOGGING; ON-LINE SOCIAL NETWORKS; ONLINE SOCIAL NETWORKS (OSNS); POTENTIAL INVESTORS; SOCIAL INTERACTIONS; SPAM;

INTERNET;

EID: 84904515492     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2615569.2615688     Document Type: Conference Paper

References (38)

1. A. Almaatouq, F. Alhasoun, R. Campari, and A. Alfaris. The influence of social norms on synchronous versus asynchronous communication technologies. In Proceedings of the 1st ACM International Workshop on Personal Data Meets Distributed Multimedia, PDM '13, pages 39-42, New York, NY, USA, 2013. ACM.
2. Y. Altshuler, N. Aharony, A. Pentland, Y. Elovici, and M. Cebrian. Stealing reality: When criminals become data scientists (or vice versa). IEEE Intelligent Systems, 26(6):22-30, 2011.
3. F. Benevenuto, G. Magno, T. Rodrigues, and V. Almeida. Detecting spammers on Twitter. In Proceedings of the Seventh Annual Collaboration, Electronic messaging, Anti-Abuse and Spam Conference (CEAS), July 2010.
4. J. Borondo, A. J. Morales, J. C. Losada, and R. M. Benito. Characterizing and modeling an electoral campaign in the context of Twitter: 2011 Spanish Presidential election as a case study. Chaos: An Interdisciplinary Journal of Nonlinear Science, 22(2), 2012.
5. U. Brandes. A faster algorithm for betweenness centrality. Journal of Mathematical Sociology, 25:163-177, 2001. (Pubitemid 33398479
6. S. Chhabra, A. Aggarwal, F. Benevenuto, and P. Kumaraguru. Phi.sh/$ocial: The phishing landscape through short urls. In Proceedings of the 8th Annual Collaboration, Electronic Messaging, Anti-Abuse and Spam Conference, CEAS '11, pages 92-101, New York, NY, USA, 2011. ACM.
7. A. Clauset, C. R. Shalizi, and M. E. J. Newman. Power-law distributions in empirical data. SIAM Rev., 51(4):661-703, Nov. 2009.
8. M. Conover, J. Ratkiewicz, M. Francisco, B. Gonçalves, A. Flammini, and F. Menczer. Political polarization on twitter. In Proc. 5th International AAAI Conference on Weblogs and Social Media (ICWSM), 2011.
9. M. Egele, G. Stringhini, C. Kruegel, and G. Vigna. COMPA: Detecting Compromised Accounts on Social Networks. In ISOC Network and Distributed System Security Symposium (NDSS), 2013.
10. L. C. Freeman. A Set of Measures of Centrality Based on Betweenness. Sociometry, 40(1):35-41, Mar. 1977.
11. S. Ghosh, B. Viswanath, F. Kooti, N. K. Sharma, G. Korlam, F. Benevenuto, N. Ganguly, and K. P. Gummadi. Understanding and combating link farming in the twitter social network. In Proceedings of the 21st International Conference on World Wide Web, WWW '12, pages 61-70, New York, NY, USA, 2012. ACM.
12. GlobalWebIndex. Global web index: Q4 2012, 2013.
13. S. González-Bailón, J. Borge-Holthoefer, A. Rivero, and Y. Moreno. The dynamics of protest recruitment through an online network.
14. C. Grier, K. Thomas, V. Paxson, and M. Zhang. @spam: The underground on 140 characters or less. In Proceedings of the 17th ACM Conference on Computer and Communications Security, CCS '10, pages 27-37, New York, NY, USA, 2010. ACM.
15. S. Kato, A. Koide, T. Fushimi, K. Saito, and H. Motoda. Network analysis of three twitter functions: Favorite, follow and mention. In D. Richards and B. Kang, editors, Knowledge Management and Acquisition for Intelligent Systems, volume 7457 of Lecture Notes in Computer Science, pages 298-312. Springer Berlin Heidelberg, 2012.
16. C. Lumezanu, N. Feamster, and H. Klein. bias: Measuring the tweeting behavior of propagandists. In ICWSM, 2012.
17. A. Marcus, M. S. Bernstein, O. Badar, D. R. Karger, S. Madden, and R. C. Miller. Twitinfo: Aggregating and visualizing microblogs for event exploration. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI '11, pages 227-236, New York, NY, USA, 2011. ACM.
18. M. McCord and M. Chuah. Spam detection on twitter using traditional classifiers. In Proceedings of the 8th international conference on Autonomic and trusted computing, ATC'11, pages 175-186, Berlin, Heidelberg, 2011. Springer-Verlag.
19. F. Morstatter, J. Pfeffer, H. Liu, and K. M. Carley. Is the sample good enough? comparing data from Twitter's streaming API with Twitter's Firehose. Proceedings of ICWSM, 2013.
20. M. E. J. Newman. Power laws, pareto distributions and zipf's law. Contemporary Physics, 46:323-351, December 2005.
21. H. Nguyen. 2013 state of social media spam. Technical report, Nexgate, 2013.
22. A. Sanzgiri, A. Hughes, and S. Upadhyaya. Analysis of malware propagation in twitter. Reliable Distributed Systems, IEEE Symposium on, 0:195-204, 2013.
23. G. Stringhini, M. Egele, C. Kruegel, and G. Vigna. Poultry markets: On the underground economy of twitter followers. In Proceedings of the 2012 ACM Workshop on Workshop on Online Social Networks, WOSN '12, pages 1-6, New York, NY, USA, 2012. ACM.
24. G. Stringhini, C. Kruegel, and G. Vigna. Detecting spammers on social networks. Proceedings of the 26th Annual Computer Security Applications Conference on -ACSAC '10, page 1, 2010.
25. M. Thelwall, K. Buckley, and G. Paltoglou. Sentiment in twitter events. J. Am. Soc. Inf. Sci. Technol., 62(2):406-418, Feb. 2011.
26. K. Thomas, C. Grier, and V. Paxson. Adapting Social Spam Infrastructure for Political Censorship. In Proceedings of the 5th USENIX Workshop on Large-Scale Exploits and Emergent Threats (LEET), Apr. 2012.
27. K. Thomas, C. Grier, D. Song, and V. Paxson. Suspended accounts in retrospect: an analysis of twitter spam. In Proceedings of the 2011 ACM SIGCOMM conference on Internet measurement conference, IMC '11, pages 243-258, New York, NY, USA, 2011. ACM.
28. K. Thomas, D. McCoy, C. Grier, A. Kolcz, and V. Paxson. Trafficking fraudulent accounts: The role of the underground market in twitter spam and abuse. In Proceedings of the 22nd Usenix Security Symposium, 2013.
29. Twitter. Following rules and best practices. https://support.twitter.com/ articles/68916-following-rules-And-best-practices, 2012. [Online; accessed 22-October-2013].
30. Twitter. Public stream. https://dev.twitter.com/docs/streaming-Apis/, 2012. [Online; accessed 1-October-2013].
31. Twitter. Rules. https://support.twitter.com/articles/18311-The-Twitter- rules, 2012. [Online; accessed 1-October-2013].
32. Twitter. Initial public offering of shares of common stock of twitter, inc. http://www.sec.gov/Archives/edgar/data/1418091/000119312513390321/ d564001ds1.htm, 2013. [Online; accessed 5-October-2013].
33. A. H. Wang. Don't follow me: Spam detection in twitter. In Security and Cryptography (SECRYPT), Proceedings of the 2010 International Conference on, pages 1-10, 2010.
34. G. Wang, M. Mohanlal, C. Wilson, X. Wang, M. J. Metzger, H. Zheng, and B. Y. Zhao. Social turing tests: Crowdsourcing sybil detection. In NDSS. The Internet Society, 2013.
35. Y. Xie, F. Yu, Q. Ke, M. Abadi, E. Gillum, K. Vitaldevaria, J. Walter, J. Huang, and Z. M. Mao. Innocent by association: Early recognition of legitimate users. In Proceedings of the 2012 ACM Conference on Computer and Communications Security, CCS '12, pages 353-364, New York, NY, USA, 2012. ACM.
36. C. Yang, R. Harkreader, and G. Gu. Die free or live hard? empirical evaluation and new design for fighting evolving twitter spammers. In R. Sommer, D. Balzarotti, and G. Maier, editors, Recent Advances in Intrusion Detection, volume 6961 of Lecture Notes in Computer Science, pages 318-337. Springer Berlin Heidelberg, 2011.
37. C. Yang, R. Harkreader, J. Zhang, S. Shin, and G. Gu. Analyzing spammers' social networks for fun and profit: a case study of cyber criminal ecosystem on twitter. In Proceedings of the 21st international conference on World Wide Web, WWW '12, pages 71-80, New York, NY, USA, 2012. ACM.
38. C. M. Zhang and V. Paxson. Detecting and analyzing automated activity on twitter. In Proceedings of the 12th international conference on Passive and active measurement, PAM'11, pages 102-111, Berlin, Heidelberg, 2011. Springer-Verlag.