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标题：Analysis and Design of Efficient generalized Forensic framework for Detecting Twitter Spammers
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作者：Ankita M. Ghate ; L. G. Malik
期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2015
卷号：3
期号：3
DOI：10.15680/ijircce.2015.0303102
出版社：S&S Publications
摘要：Asocial networking web site could be a platform to make social networks or social relationsamong those who share interests, activities, backgrounds or real-life connections. Users pay a good deal of yourtime on known social networks(e.g.Facebook,Twitter, SinaWeibo, etc.), reading news, discussing events and postingtheir message. Unfortunately, this quality conjointly attracts a big quantity of spammers whoincessantly exposemalicious behaviours (e.g. post messages containing commercial topics or URLs, following a bigger quantity of users,etc.), resulting in nice inconvenience on traditional users’ social activities. The propose system will workAIER(Artificial intelligence for emergency response) approach for detecting twitter spammer .We first collected and labelleda large dataset with 34 K trending topics and 20 million tweets then, construct a labelled dataset of users and manuallyclassify users into spammers and non-spammers; after that, abstract a set of novel features from message content andusers’ social behavior. Our experiments show that true positive rate of spammers and non-spammers could reach 99.1%and 99.9%.
关键词：Twitter;ArtificialIntelligence;Data Collection Log Data collection spammers; network forensic