Processing Affect in Social Media A Comparison of Methods to Distinguish Emotions in Tweets

Emotion analysis in social media is challenging. While most studies focus on positive and negative sentiments, the differentiation between emotions is more difficult. We investigate the problem as a collection of binary classification tasks on the basis of four opposing emotion pairs provided by Plu...

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Bibliographic Details
Published inACM transactions on Internet technology Vol. 17; no. 1; pp. 1 - 25
Main Authors Meo, Rosa, Sulis, Emilio
Format Journal Article
LanguageEnglish
Published 01.03.2017
Subjects
Classification
Collection
Digital media
Emotions
Messages
Natural language processing
Social networks
Tasks
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Summary:Emotion analysis in social media is challenging. While most studies focus on positive and negative sentiments, the differentiation between emotions is more difficult. We investigate the problem as a collection of binary classification tasks on the basis of four opposing emotion pairs provided by Plutchik. We processed the content of messages by three alternative methods: structural and lexical features, latent factors, and natural language processing. The final prediction is suggested by classifiers deriving from the state of the art in machine learning. Results are convincing in the possibility to distinguish the emotions pairs in social media.
Bibliography:ObjectType-Article-1
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ISSN:1533-5399
1557-6051
DOI:10.1145/2996187