What are tweeters doing: Recognizing speech acts in twitter

Renxian Zhang, Dehong Gao, Wenjie Li

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

18 Citations (Scopus)

Abstract

Speech acts provide good insights into the communicative behavior of tweeters on Twitter. This paper is mainly concerned with speech act recognition in Twitter as a multi-class classification problem, for which we propose a set of word-based and character-based features. Inexpensive, robust and efficient, our method achieves an average Fl score of nearly 0.7 with the existence of much noise in our annotated Twitter data. In view of the deficiency of training data for the task, we experimented extensively with different configurations of training and test data, leading to empirical findings that may provide valuable reference for building benchmark datasets for sustained research on speech act recognition in Twitter.
Original languageEnglish
Title of host publicationAnalyzing Microtext - Papers from the 2011 AAAI Workshop, Technical Report
Pages86-91
Number of pages6
VolumeWS-11-05
Publication statusPublished - 31 Oct 2011
Event2011 AAAI Workshop - San Francisco, CA, United States
Duration: 8 Aug 20118 Aug 2011

Conference

Conference2011 AAAI Workshop
Country/TerritoryUnited States
CitySan Francisco, CA
Period8/08/118/08/11

ASJC Scopus subject areas

  • Engineering(all)

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