Difference between revisions of "Yang et. al., SIGKDD 2012"
From Cohen Courses
Jump to navigationJump to search| Line 9: | Line 9: | ||
== Summary == | == Summary == | ||
| − | This [[Category::Paper]] addresses the problem of [[AddressesProblem::Rumor Detection]] in Weibo (equivalent to Twitter in Mainland China). | + | 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. |
| + | |||
| + | 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 18:40, 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.
