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        <title>PLN-PUCRS at EmoInt-2017: Psycholinguistic features for emotion intensity prediction in tweets</title>
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        <name type="personal">
            <namePart type="given">Alexandra</namePart>
            <namePart type="family">Balahur</namePart>
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        <name type="personal">
            <namePart type="given">Saif</namePart>
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            <namePart type="given">Erik</namePart>
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    <abstract>Linguistic Inquiry and Word Count (LIWC) is a rich dictionary that map words into several psychological categories such as Affective, Social, Cognitive, Perceptual and Biological processes. In this work, we have used LIWC psycholinguistic categories to train regression models and predict emotion intensity in tweets for the EmoInt-2017 task. Results show that LIWC features may boost emotion intensity prediction on the basis of a low dimension set.</abstract>
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%0 Conference Proceedings
%T PLN-PUCRS at EmoInt-2017: Psycholinguistic features for emotion intensity prediction in tweets
%A Santos, Henrique
%A Vieira, Renata
%Y Balahur, Alexandra
%Y Mohammad, Saif M.
%Y van der Goot, Erik
%S Proceedings of the 8th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis
%D 2017
%8 September
%I Association for Computational Linguistics
%C Copenhagen, Denmark
%F santos-vieira-2017-pln
%X Linguistic Inquiry and Word Count (LIWC) is a rich dictionary that map words into several psychological categories such as Affective, Social, Cognitive, Perceptual and Biological processes. In this work, we have used LIWC psycholinguistic categories to train regression models and predict emotion intensity in tweets for the EmoInt-2017 task. Results show that LIWC features may boost emotion intensity prediction on the basis of a low dimension set.
%R 10.18653/v1/W17-5225
%U https://aclanthology.org/W17-5225
%U https://doi.org/10.18653/v1/W17-5225
%P 189-192

Markdown (Informal)

[PLN-PUCRS at EmoInt-2017: Psycholinguistic features for emotion intensity prediction in tweets](https://aclanthology.org/W17-5225) (Santos & Vieira, WASSA 2017)

• PLN-PUCRS at EmoInt-2017: Psycholinguistic features for emotion intensity prediction in tweets (Santos & Vieira, WASSA 2017)

ACL

• Henrique Santos and Renata Vieira. 2017. PLN-PUCRS at EmoInt-2017: Psycholinguistic features for emotion intensity prediction in tweets. In Proceedings of the 8th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, pages 189–192, Copenhagen, Denmark. Association for Computational Linguistics.