Analysis and identification of spamming behaviors in Sina Weibo microblog

Chengfeng Lin, Jianhua He, Yi Zhou, Xiaokang Yang, Kai Chen, Li Song

Research output: Chapter in Book/Report/Conference proceedingConference publication

Abstract

Spamming has been a widespread problem for social networks. In recent years there is an increasing interest in the analysis of anti-spamming for microblogs, such as Twitter. In this paper we present a systematic research on the analysis of spamming in Sina Weibo platform, which is currently a dominant microblogging service provider in China. Our research objectives are to understand the specific spamming behaviors in Sina Weibo and find approaches to identify and block spammers in Sina Weibo based on spamming behavior classifiers. To start with the analysis of spamming behaviors we devise several effective methods to collect a large set of spammer samples, including uses of proactive honeypots and crawlers, keywords based searching and buying spammer samples directly from online merchants. We processed the database associated with these spammer samples and interestingly we found three representative spamming behaviors: Aggressive advertising, repeated duplicate reposting and aggressive following. We extract various features and compare the behaviors of spammers and legitimate users with regard to these features. It is found that spamming behaviors and normal behaviors have distinct characteristics. Based on these findings we design an automatic online spammer identification system. Through tests with real data it is demonstrated that the system can effectively detect the spamming behaviors and identify spammers in Sina Weibo.

Original languageEnglish
Title of host publicationProceedings of the 7th workshop on Social Network Mining and Analysis, SNA-KDD 2013
Place of PublicationNew York, NY (US)
PublisherACM
ISBN (Print)978-1-450-32330-7
DOIs
Publication statusPublished - 1 Aug 2013
Event7th workshop on Social Network mining and Analysis / 19th ACM SIGKDD international conference on Knowldge Dicovery and Data mining - Chicago, IL, United States
Duration: 11 Aug 201314 Aug 2013

Workshop

Workshop7th workshop on Social Network mining and Analysis / 19th ACM SIGKDD international conference on Knowldge Dicovery and Data mining
Abbreviated titleSNA KDD 2013
CountryUnited States
CityChicago, IL
Period11/08/1314/08/13

Keywords

  • automatic spammer identification
  • crawlers
  • proactive honeypots
  • Sina Weibo
  • spamming behaviors

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  • Cite this

    Lin, C., He, J., Zhou, Y., Yang, X., Chen, K., & Song, L. (2013). Analysis and identification of spamming behaviors in Sina Weibo microblog. In Proceedings of the 7th workshop on Social Network Mining and Analysis, SNA-KDD 2013 [5] ACM. https://doi.org/10.1145/2501025.2501035