Automatic fake followers detection in Chinese micro-blogging system

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 8444 LNAI, Issue PART 2, 2014, Pages 596-607

  Shen, Yi ^a,b   Yu, Jianjun ^b   Dong, Kejun ^b   Nan, Kai ^b  

^a UNIVERSITY OF CHINESE ACADEMY OF SCIENCES   (China)

^b INSTITUTE OF GEOLOGY AND GEOPHYSICS   (China)

Author keywords

Classification; Fake followers; Feature extraction; Micro blogging

Indexed keywords

CLASSIFICATION (OF INFORMATION); DATA MINING; FEATURE EXTRACTION; POLLUTION;

BINARY CLASSIFIERS; FAKE FOLLOWERS; LEGITIMATE USERS; MICRO-BLOGGING; MICRO-BLOGGING PLATFORMS; SINA-WEIBO; SOCIAL MEDIA NETWORKS;

BLOGS;

EID: 84901249666     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-319-06605-9_49     Document Type: Conference Paper

References (21)

1. Stringhini, G., Kruegel, C., Vigna, G.: Detecting spammers on social networks. In: ACSAC 2010 Conference Proceedings, pp. 1-9 (2010)
2. Kwak, H., Lee, C., Park, H., Moon, S.: What is twitter, a social network or a news media? In: WWW 2010 Conference Proceedings, pp. 591-600 (2010)
3. Qazvinian, V., Rosengren, E., Radev, D.R., Mei, Q.: Rumor has it: identifying misinformation in microblogs. In: EMNLP 2011 Conference Proceedings, pp. 1589-1599 (2011)
4. Mendoza, M., Poblete, B., Castillo, C.: Twitter under crisis: Can we trust what we rt? In: Proceedings of the First Workshop on Social Media Analytics, pp. 71-79 (2010)
5. Grier, C., Thomas, K., Paxson, V., Zhang, M.: @spam: the underground on 140 characters or less. In: CCS 2010 Conference Proceedings, pp. 27-37 (2010)
6. McCord, M., Chuah, M.: Spam detection on twitter using traditional classifiers. In: Calero, J.M.A., Yang, L.T., Mármol, F.G., García Villalba, L.J., Li, A.X.,Wang, Y. (eds.) ATC 2011. LNCS, vol. 6906, pp. 175-186. Springer, Heidelberg (2011)
7. Egele, M., Stringhini, G., Kruegel, C., Vigna, G.: Compa: Detecting compromised accounts on social networks. In: Symposium on Network and Distributed System Security, NDSS (2013)
8. Gao, H., Hu, J., Wilson, C., Li, Z., Chen, Y., Zhao, B.Y.: Detecting and characterizing social spam campaigns. In: IMC 2010 Conference Proceedings, pp. 35-47 (2010)
9. Stringhini, G., Egele, M., Kruegel, C., Vigna, G.: Poultry markets: On the underground economy of twitter followers. In: WOSN 2012 Conference Proceedings, pp. 1-6 (2012)
10. Ghosh, S., Viswanath, B., Kooti, F., Sharma, N.K., Korlam, G., Benevenuto, F., Ganguly, N., Gummadi, K.P.: Understanding and combating link farming in the twitter social network. In: WWW 2012 Conference Proceedings, pp. 61-70 (2012)
11. Thomas, K., Grier, C., Song, D., Paxson, V.: Suspended accounts in retrospect: an analysis of twitter spam. In: IMC 2011 Conference Proceedings, pp. 243-258 (2011)
12. Yang, C., Harkreader, R., Zhang, J., Shin, S., Gu, G.: Analyzing spammers' social networks for fun and profit: a case study of cyber criminal ecosystem on twitter. In: WWW 2012 Conference Proceedings, pp. 71-80 (2012)
13. Benevenuto, F., Magno, G., Rodrigues, T., Almeida, V.: Detecting spammers on twitter. In: Collaboration, Electronic Messaging, Anti-abuse and Spam Conference (CEAS), vol. 6 (2010)
14. Lee, K., Caverlee, J., Webb, S.: Uncovering social spammers: social honeypots+ machine learning. In: SIGIR 2010 Conference Proceedings, pp. 435-442 (2010)
15. Zhu, Y., Wang, X., Zhong, E., Liu, N.N., Li, H., Yang, Q.: Discovering spammers in social networks. In: AAAI 2012 Conference Proceedings, pp. 171-177 (2012)
16. Cha, M., Haddadi, H., Benevenuto, F., Gummadi, P.K.: Measuring user influence in twitter: The million follower fallacy. ICWSM 10, 10-17 (2010)
17. Rosen-Zvi, M., Griffiths, T., Steyvers, M., Smyth, P.: The author-topic model for authors and documents. In: UAI 2004 Conference Proceedings, pp. 487-494 (2004)
18. Chang, J., Gerrish, S., Wang, C., Boyd-graber, J.L., Blei, D.M.: Reading tea leaves: How humans interpret topic models. In: Advances in Neural Information Processing Systems, pp. 288-296 (2009)
19. Kwak, H., Chun, H., Moon, S.: Fragile online relationship: a first look at unfollow dynamics in twitter. In: CHI 2011 Conference Proceedings, pp. 1091-1100 (2011)
20. Chang, C.C., Lin, C.J.: Libsvm: a library for support vector machines. ACM Transactions on Intelligent Systems and Technology (TIST) 2, 1-27 (2011)
21. Quinlan, J.R.: Bagging, boosting, and c4. 5. In: AAAI/IAAI, vol. 1, pp. 725-730 (1996)