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CIKM
2011
Springer

Content-driven detection of campaigns in social media

8 years 2 months ago
Content-driven detection of campaigns in social media
We study the problem of detecting coordinated free text campaigns in large-scale social media. These campaigns – ranging from coordinated spam messages to promotional and advertising campaigns to political astro-turfing – are growing in significance and reach with the commensurate rise of massive-scale social systems. Often linked by common “talking points”, there has been little research in detecting these campaigns. Hence, we propose and evaluate a contentdriven framework for effectively linking free text posts with common “talking points” and extracting campaigns from large-scale social media. One of the salient aspects of the framework is an investigation of graph mining techniques for isolating coherent campaigns from large message-based graphs. Through an experimental study over millions of Twitter messages we identify five major types of campaigns – Spam, Promotion, Template, News, and Celebrity campaigns – and we show how these campaigns may be extracted wi...
Kyumin Lee, James Caverlee, Zhiyuan Cheng, Daniel
Added 13 Dec 2011
Updated 13 Dec 2011
Type Journal
Year 2011
Where CIKM
Authors Kyumin Lee, James Caverlee, Zhiyuan Cheng, Daniel Z. Sui
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