HSpam14: A Collection of 14 Million Tweets for Hashtag-Oriented Spam Research
暂无分享,去创建一个
[1] Filippo Menczer,et al. The rise of social bots , 2014, Commun. ACM.
[2] Krishna P. Gummadi,et al. Understanding and combating link farming in the twitter social network , 2012, WWW.
[3] Claire Cardie,et al. TopicSpam: a Topic-Model based approach for spam detection , 2013, ACL.
[4] Kyumin Lee,et al. Seven Months with the Devils: A Long-Term Study of Content Polluters on Twitter , 2011, ICWSM.
[5] Claire Cardie,et al. Finding Deceptive Opinion Spam by Any Stretch of the Imagination , 2011, ACL.
[6] Zhe Wang,et al. Filtering Image Spam with Near-Duplicate Detection , 2007, CEAS.
[7] Huan Liu,et al. Online Social Spammer Detection , 2014, AAAI.
[8] Junhui Wang,et al. Detecting group review spam , 2011, WWW.
[9] Huan Liu,et al. Leveraging knowledge across media for spammer detection in microblogging , 2014, SIGIR.
[10] Bing Liu,et al. Review spam detection , 2007, WWW '07.
[11] Vern Paxson,et al. @spam: the underground on 140 characters or less , 2010, CCS '10.
[12] Yi Yang,et al. Learning to Identify Review Spam , 2011, IJCAI.
[13] Dawn Xiaodong Song,et al. Suspended accounts in retrospect: an analysis of twitter spam , 2011, IMC '11.
[14] Gilad Mishne,et al. Blocking Blog Spam with Language Model Disagreement , 2005, AIRWeb.
[15] Virgílio A. F. Almeida,et al. Detecting Spammers and Content Promoters in Online Video Social Networks , 2009, IEEE INFOCOM Workshops 2009.
[16] Ee-Peng Lim,et al. Detecting product review spammers using rating behaviors , 2010, CIKM.
[17] Ophir Frieder,et al. Collection statistics for fast duplicate document detection , 2002, TOIS.
[18] Ping Li,et al. In Defense of Minhash over Simhash , 2014, AISTATS.
[19] Andrei Z. Broder,et al. On the resemblance and containment of documents , 1997, Proceedings. Compression and Complexity of SEQUENCES 1997 (Cat. No.97TB100171).
[20] Sebastian Thrun,et al. Text Classification from Labeled and Unlabeled Documents using EM , 2000, Machine Learning.
[21] Christopher D. Manning,et al. Introduction to Information Retrieval , 2010, J. Assoc. Inf. Sci. Technol..
[22] Qi He,et al. TwitterRank: finding topic-sensitive influential twitterers , 2010, WSDM '10.
[23] Georgia Koutrika,et al. Fighting Spam on Social Web Sites: A Survey of Approaches and Future Challenges , 2007, IEEE Internet Computing.
[24] Byron Choi,et al. Detecting spam blogs from blog search results , 2011, Inf. Process. Manag..
[25] Kyumin Lee,et al. The Dark Side of Micro-Task Marketplaces: Characterizing Fiverr and Automatically Detecting Crowdturfing , 2014, ICWSM.
[26] Virgílio A. F. Almeida,et al. Detecting Spammers on Twitter , 2010 .
[27] Douglas W. Oard,et al. Reducing Reliance on Relevance Judgments for System Comparison by Using Expectation-Maximization , 2014, ECIR.
[28] Songqing Chen,et al. UNIK: unsupervised social network spam detection , 2013, CIKM.
[29] Markus Strohmaier,et al. When Social Bots Attack: Modeling Susceptibility of Users in Online Social Networks , 2012, #MSM.
[30] Fabrício Benevenuto,et al. You followed my bot! Transforming robots into influential users in Twitter , 2013, First Monday.
[31] Bing Liu,et al. Opinion spam and analysis , 2008, WSDM '08.
[32] Gang Wang,et al. Serf and turf: crowdturfing for fun and profit , 2011, WWW.
[33] V. Paxson,et al. The Underground on 140 Characters or Less ∗ , 2010 .
[34] Tat-Seng Chua,et al. NUS-WIDE: a real-world web image database from National University of Singapore , 2009, CIVR '09.
[35] Sushil Jajodia,et al. Who is tweeting on Twitter: human, bot, or cyborg? , 2010, ACSAC '10.
[36] Philip S. Yu,et al. Building text classifiers using positive and unlabeled examples , 2003, Third IEEE International Conference on Data Mining.
[37] Barbara Poblete,et al. Information credibility on twitter , 2011, WWW.
[38] Gordon V. Cormack,et al. Email Spam Filtering: A Systematic Review , 2008, Found. Trends Inf. Retr..
[39] Tim Oates,et al. Ensembles in adversarial classification for spam , 2009, CIKM.
[40] Jiawei Han,et al. Survey on web spam detection: principles and algorithms , 2012, SKDD.
[41] Kyumin Lee,et al. The social honeypot project: protecting online communities from spammers , 2010, WWW '10.
[42] Kyumin Lee,et al. Characterizing and automatically detecting crowdturfing in Fiverr and Twitter , 2015, Social Network Analysis and Mining.