#Emotional Tweets

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Proceedings titleProceedings of First Joint Conference on Lexical and Computational Semantics (*Sem)
ConferenceFirst Joint Conference on Lexical and Computational Semantics (*Sem), June 7-8, 2012, Montreal, Quebec, Canada
Pages246255; # of pages: 10
AbstractDetecting emotions in microblogs and social media posts has applications for industry, health, and security. However, there exists no microblog corpus with instances labeled for emotions for developing supervised systems. In this paper, we describe how we created such a corpus from Twitter posts using emotionword hashtags. We conduct experiments to show that the self-labeled hashtag annotations are consistent and match with the annotations of trained judges. We also show how the Twitter emotion corpus can be used to improve emotion classification accuracy in a different domain. Finally, we extract a word–emotion association lexicon from this Twitter corpus, and show that it leads to significantly better results than the manually crafted WordNet Affect lexicon in an emotion classification task.
Publication date
PublisherAssociation for Computational Linguistics (ACL)
AffiliationInformation and Communication Technologies; National Research Council Canada
Peer reviewedYes
NPARC number20833317
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Record identifier36edfec2-bcd9-427f-9812-201e6d192fbf
Record created2012-10-22
Record modified2016-05-09
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