Badly Evolved? Exploring Long-Surviving Suspicious Users on Twitter
暂无分享,去创建一个
[1] Barbara Poblete,et al. Information credibility on twitter , 2011, WWW.
[2] Eni Mustafaraj,et al. From Obscurity to Prominence in Minutes: Political Speech and Real-Time Search , 2010 .
[3] Huan Liu,et al. The fragility of Twitter social networks against suspended users , 2015, 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM).
[4] Leo Breiman,et al. Random Forests , 2001, Machine Learning.
[5] Michael J. Franklin,et al. Resilient Distributed Datasets: A Fault-Tolerant Abstraction for In-Memory Cluster Computing , 2012, NSDI.
[6] Chao Yang,et al. Empirical Evaluation and New Design for Fighting Evolving Twitter Spammers , 2011, IEEE Transactions on Information Forensics and Security.
[7] J. M. Berger,et al. The ISIS Twitter census: defining and describing the population of ISIS supporters on Twitter , 2015 .
[8] Kyumin Lee,et al. Uncovering social spammers: social honeypots + machine learning , 2010, SIGIR.
[9] Vern Paxson,et al. @spam: the underground on 140 characters or less , 2010, CCS '10.
[10] Dawn Xiaodong Song,et al. Suspended accounts in retrospect: an analysis of twitter spam , 2011, IMC '11.
[11] Ameet Talwalkar,et al. MLlib: Machine Learning in Apache Spark , 2015, J. Mach. Learn. Res..
[12] Alex Hai Wang,et al. Don't follow me: Spam detection in Twitter , 2010, 2010 International Conference on Security and Cryptography (SECRYPT).
[13] Filippo Menczer,et al. BotOrNot: A System to Evaluate Social Bots , 2016, WWW.
[14] Michael I. Jordan,et al. Latent Dirichlet Allocation , 2001, J. Mach. Learn. Res..
[15] Jacob Ratkiewicz,et al. Detecting and Tracking Political Abuse in Social Media , 2011, ICWSM.
[16] Alessandro Flammini,et al. Predicting online extremism, content adopters, and interaction reciprocity , 2016, SocInfo.
[17] Cheng Soon Ong,et al. Multivariate spearman's ρ for aggregating ranks using copulas , 2016 .
[18] Jure Leskovec,et al. No country for old members: user lifecycle and linguistic change in online communities , 2013, WWW.
[19] Leysia Palen,et al. (How) will the revolution be retweeted?: information diffusion and the 2011 Egyptian uprising , 2012, CSCW.
[20] Vern Paxson,et al. Adapting Social Spam Infrastructure for Political Censorship , 2012, LEET.
[21] Jong Kim,et al. Spam Filtering in Twitter Using Sender-Receiver Relationship , 2011, RAID.
[22] D. Boyd,et al. The Arab Spring| The Revolutions Were Tweeted: Information Flows during the 2011 Tunisian and Egyptian Revolutions , 2011 .
[23] Virgílio A. F. Almeida,et al. Detecting Spammers on Twitter , 2010 .
[24] Margaret E. Roberts,et al. How the Chinese Government Fabricates Social Media Posts for Strategic Distraction, Not Engaged Argument , 2017, American Political Science Review.
[25] Huan Liu,et al. Social Spammer Detection in Microblogging , 2013, IJCAI.
[26] Slava M. Katz,et al. Estimation of probabilities from sparse data for the language model component of a speech recognizer , 1987, IEEE Trans. Acoust. Speech Signal Process..
[27] Jacob Ratkiewicz,et al. Political Polarization on Twitter , 2011, ICWSM.
[28] Po-Ching Lin,et al. A study of effective features for detecting long-surviving Twitter spam accounts , 2013, 2013 15th International Conference on Advanced Communications Technology (ICACT).
[29] Gianluca Stringhini,et al. Detecting spammers on social networks , 2010, ACSAC '10.