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A Practical Guide to Sentiment AnalysisSentiment Resources: Lexicons and Datasets

A Practical Guide to Sentiment Analysis: Sentiment Resources: Lexicons and Datasets [Sentiment lexicons and datasets represent the knowledge base that lies at the foundation of a SA system. In its simplest form, a sentiment lexicon is a repository of words/phrases labelled with sentiment. Similarly, a sentiment-annotated dataset consists of documents (tweets, sentences or longer documents) labelled with one or more sentiment labels. This chapter explores the philosophy, execution and utility of popular sentiment lexicons and datasets. We describe different labelling schemes that may be used. We then provide a detailed description of existing sentiment and emotion lexicons, and the trends underlying research in lexicon generation. This is followed by a survey of sentiment-annotated datasets and the nuances of labelling involved. We then show how lexicons and datasets created for one language can be transferred to a new language. Finally, we place these sentiment resources in the perspective of their classic applications to sentiment analysis.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

A Practical Guide to Sentiment AnalysisSentiment Resources: Lexicons and Datasets

Part of the Socio-Affective Computing Book Series (volume 5)
Editors: Cambria, Erik; Das, Dipankar; Bandyopadhyay, Sivaji; Feraco, Antonio
Joshi, Aditya; Bhattacharyya, Pushpak; Ahire, Sagar
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
85 –106
DOI
10.1007/978-3-319-55394-8_5
Publisher site
See Chapter on Publisher Site

Abstract

[Sentiment lexicons and datasets represent the knowledge base that lies at the foundation of a SA system. In its simplest form, a sentiment lexicon is a repository of words/phrases labelled with sentiment. Similarly, a sentiment-annotated dataset consists of documents (tweets, sentences or longer documents) labelled with one or more sentiment labels. This chapter explores the philosophy, execution and utility of popular sentiment lexicons and datasets. We describe different labelling schemes that may be used. We then provide a detailed description of existing sentiment and emotion lexicons, and the trends underlying research in lexicon generation. This is followed by a survey of sentiment-annotated datasets and the nuances of labelling involved. We then show how lexicons and datasets created for one language can be transferred to a new language. Finally, we place these sentiment resources in the perspective of their classic applications to sentiment analysis.]

Published: Apr 12, 2017

Keywords: Sentiment lexicons; Sentiment datasets; Evaluation; Transfer learning

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