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Dictionary-Based Sentiment Analysis Applied to a Specific Domain

  • 2017
  • OriginalPaper
  • Chapter
Published in:
Authors
Laura Cruz
José Ochoa
Mathieu Roche
Pascal Poncelet
Published in
Information Management and Big Data
Publisher
Springer International Publishing

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Abstract

The web and social media have been growing exponentially in recent years. We now have access to documents bearing opinions expressed on a broad range of topics. This constitutes a rich resource for natural language processing tasks, particularly for sentiment analysis. Nevertheless, sentiment analysis is usually difficult because expressed sentiments are usually topic-oriented. In this paper, we propose to automatically construct a sentiment dictionary using relevant terms obtained from web pages for a specific domain. This dictionary is initially built by querying the web with a combination of opinion terms, as well as terms of the domain. In order to select only relevant terms we apply two measures \(\textit{AcroDef}_{\textit{MI}3}\) and TrueSkill. Experiments conducted on different domains highlight that our automatic approach performs better for specific cases.

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previous chapter Network Sampling Based on Centrality Measures for Relational Classification
next chapter A Clustering Optimization Approach for Disaster Relief Delivery: A Case Study in Lima-Perú
Title
Dictionary-Based Sentiment Analysis Applied to a Specific Domain
Authors
Laura Cruz
José Ochoa
Mathieu Roche
Pascal Poncelet
Copyright Year
2017
Book
Information Management and Big Data

Print ISBN: 978-3-319-55208-8

Electronic ISBN: 978-3-319-55209-5

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-55209-5_5
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