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Dictionary-Based Sentiment Analysis Applied to a Specific Domain

  • Laura Cruz
  • José Ochoa
  • Mathieu Roche
  • Pascal Poncelet
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 656)

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.

Keywords

Text mining Web mining Sentiment analysis 

Notes

Acknowledgement

This work has been supported and funded by FONDECYT and SONGES project (http://textmining.biz/Projects/Songes) (FEDER and Occitanie).

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Universidad Nacional de San AgustínArequipaPeru
  2. 2.Universidad Católica San PabloArequipaPeru
  3. 3.TETIS (CIRAD, CNRS, AgroParisTech, Irstea)ParisFrance
  4. 4.LIRMM (CNRS, Univ. Montpellier)MontpellierFrance

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