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Sentiment Analysis

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Text Mining for Information Professionals

Abstract

Sentiment or opinion analysis employs natural language processing to extract a significant pattern of knowledge from a large amount of textual data. It examines comments, opinions, emotions, beliefs, views, questions, preferences, attitudes, and requests communicated by the writer in a string of text. It extracts the writer’s feelings in the form of subjectivity (objective and subjective), polarity (negative, positive, and neutral), and emotions (angry, happy, surprised, sad, jealous, and mixed). Thus, this chapter covers the theoretical framework and use cases of sentiment analysis in libraries. The chapter is followed by a case study showing the application of sentiment analysis in libraries using two different tools.

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Authors and Affiliations

  1. Library and Information Science, University of Delhi, Delhi, India

    Manika Lamba & Margam Madhusudhan

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  1. Manika Lamba
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  2. Margam Madhusudhan
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Lamba, M., Madhusudhan, M. (2022). Sentiment Analysis. In: Text Mining for Information Professionals. Springer, Cham. https://doi.org/10.1007/978-3-030-85085-2_7

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  • DOI: https://doi.org/10.1007/978-3-030-85085-2_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-85084-5

  • Online ISBN: 978-3-030-85085-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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