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A Practical Guide to Sentiment AnalysisSocial Media Summarization

A Practical Guide to Sentiment Analysis: Social Media Summarization [Social media is an important venue for information sharing, discussions or conversations on a variety of topics and events generated or happening across the globe. Application of automated text summarization techniques on the large volume of information piled up in social media can produce textual summaries in a variety of flavors depending on the difficulty of the use case. This chapter talks about the available set of techniques to generate summaries from different genres of social media text with an extensive introduction to extractive summarization techniques.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

A Practical Guide to Sentiment AnalysisSocial Media Summarization

Part of the Socio-Affective Computing Book Series (volume 5)
Editors: Cambria, Erik; Das, Dipankar; Bandyopadhyay, Sivaji; Feraco, Antonio
Varma, Vasudeva; Kurisinkel, Litton J.; Radhakrishnan, Priya
Springer Journals — Apr 12, 2017
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Publisher
Springer International Publishing
Copyright
© Springer International Publishing AG 2017. Chapter 4 is published with kind permission of the Her Majesty the Queen Right of Canada.
ISBN
978-3-319-55392-4
Pages
135 –153
DOI
10.1007/978-3-319-55394-8_7
Publisher site
See Chapter on Publisher Site

Abstract

[Social media is an important venue for information sharing, discussions or conversations on a variety of topics and events generated or happening across the globe. Application of automated text summarization techniques on the large volume of information piled up in social media can produce textual summaries in a variety of flavors depending on the difficulty of the use case. This chapter talks about the available set of techniques to generate summaries from different genres of social media text with an extensive introduction to extractive summarization techniques.]

Published: Apr 12, 2017

Keywords: Social media summarization; Extractive summarization; Conversational summarization; Event summarization; Sentiment analysis; Attribute extraction semantic similarity; Topic modeling

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