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Emotions and Personality in Personalized ServicesSentiment Analysis in Social Streams

Emotions and Personality in Personalized Services: Sentiment Analysis in Social Streams [In this chapter, we review and discuss the state of the art on sentiment analysis in social streams—such as web forums, microblogging systems, and social networks, aiming to clarify how user opinions, affective states, and intended emotional effects are extracted from user generated content, how they are modeled, and how they could be finally exploited. We explain why sentiment analysis tasks are more difficult for social streams than for other textual sources, and entail going beyond classic text-based opinion mining techniques. We show, for example, that social streams may use vocabularies and expressions that exist outside the mainstream of standard, formal languages, and may reflect complex dynamics in the opinions and sentiments expressed by individuals and communities.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Emotions and Personality in Personalized ServicesSentiment Analysis in Social Streams

Part of the Human–Computer Interaction Series Book Series
Editors: Tkalčič, Marko; De Carolis, Berardina; de Gemmis, Marco; Odić, Ante; Košir, Andrej

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References (91)

Publisher
Springer International Publishing
Copyright
© Springer International Publishing Switzerland 2016
ISBN
978-3-319-31411-2
Pages
119–140
DOI
10.1007/978-3-319-31413-6_7
Publisher site
See Chapter on Publisher Site

Abstract

[In this chapter, we review and discuss the state of the art on sentiment analysis in social streams—such as web forums, microblogging systems, and social networks, aiming to clarify how user opinions, affective states, and intended emotional effects are extracted from user generated content, how they are modeled, and how they could be finally exploited. We explain why sentiment analysis tasks are more difficult for social streams than for other textual sources, and entail going beyond classic text-based opinion mining techniques. We show, for example, that social streams may use vocabularies and expressions that exist outside the mainstream of standard, formal languages, and may reflect complex dynamics in the opinions and sentiments expressed by individuals and communities.]

Published: Jul 14, 2016

Keywords: Sentiment Analysis; Social Media Platform; Sentiment Lexicon; Affective Information; Pointwise Mutual Information

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