Difference between revisions of "Yang et. al., SIGKDD 2012"

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== Summary ==
 
== Summary ==
  
This [[Category::Paper]] addresses the problem of [[AddressesProblem::Rumor Detection]] in Weibo (equivalent to Twitter in Mainland China).
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This [[Category::Paper]] addresses the problem of [[AddressesProblem::Rumor Detection]] in Weibo (equivalent to Twitter in Mainland China). A classifier is trained using manually annotated data (identified false rumors) from a rumor-busting service available in Sina Weibo.
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This study uses features applied in previous work on Twitter Rumor Detection and analyses the different effects of these features in Weibo. Furthermore, it proposes new features that improve the overall results.

Revision as of 19:40, 29 September 2012

Citation

Fan Yang, Yang Liu, Xiaohui Yu, and Min Yang. 2012. Automatic detection of rumor on Sina Weibo. In Proceedings of the ACM SIGKDD Workshop on Mining Data Semantics (MDS '12). ACM, New York, NY, USA.

Online version

Automatic detection of rumor on Sina Weibo

Summary

This Paper addresses the problem of Rumor Detection in Weibo (equivalent to Twitter in Mainland China). A classifier is trained using manually annotated data (identified false rumors) from a rumor-busting service available in Sina Weibo.

This study uses features applied in previous work on Twitter Rumor Detection and analyses the different effects of these features in Weibo. Furthermore, it proposes new features that improve the overall results.