Tweet Acts: A Speech Act Classifier for Twitter
Name
vosoughi_roy_speechact_icwsm2016.pdf
Description
Main article
Size
311.19 KB
Format
Adobe PDF
Checksum (MD5)
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Author(s)
Vosoughi, Soroush
Roy, Deb K
Date Issued
May 2016
Journal
Proceedings of the Tenth International AAAI Conference on Web and Social Media (ICWSM 2016)
Publisher
Association for the Advancement of Artificial Intelligence (AAAI)
Citation
Vosoughi, Soroush, and Deb Roy. "Tweet Acts: A Speech Act Classifier for Twitter." Tenth International AAAI Conference on Web and Social Media (ICWSM 2016), Cologne, Germany, 17-20 May 2016, AAAI, pp.711-714.
Version
Author's final manuscript
Abstract
Speech acts are a way to conceptualize speech as action. This holds true for communication on any platform, including social media platforms such as Twitter. In this paper, we explored speech act recognition on Twitter by treating it as a multi-class classification problem. We created a taxonomy of six speech acts for Twitter and proposed a set of semantic and syntactic features. We trained and tested a logistic regression classifier using a data set of manually labelled tweets. Our method achieved a state-of-the-art performance with an average F1 score of more than 0.70. We also explored classifiers with three different granularities (Twitter-wide, type-specific and topic-specific) in order to find the right balance between generalization and overfitting for our task.
MIT Department
Program in Media Arts and Sciences (Massachusetts Institute of Technology)
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
http://www.aaai.org/ocs/index.php/ICWSM/ICWSM16/paper/view/13171/12837
