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Sentiment Analysis of Movie Reviews Using R

  • Murugan Anandarajan
  • Chelsey Hill
  • Thomas Nolan
Chapter
Part of the Advances in Analytics and Data Science book series (AADS, volume 2)

Abstract

In this chapter, the reader is presented with a step-by-step lexicon-based sentiment analysis using the R open-source software. Using 1,000 movie reviews with sentiment classification labels, the example analysis performs sentiment analysis to assess the predictive accuracy of built-in lexicons in R. Then, a custom stop list is used and accuracy is reevaluated.

Keywords

Sentiment analysis Opinion mining Online consumer reviews (OCR) RStudio Open-source 

References

  1. Hu, M., & Liu, B. (2004, August). Mining and summarizing customer reviews. In Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 168–177). ACM.Google Scholar
  2. Mohammad, S. M., & Turney, P. D. (2013). Crowdsourcing a word–emotion association lexicon. Computational Intelligence, 29(3), 436–465.CrossRefGoogle Scholar
  3. Nielsen, F. Å. (2011). A new ANEW: Evaluation of a word list for sentiment analysis in microblogs. arXiv preprint arXiv:1103.2903.Google Scholar
  4. R Development Core Team. (2008). R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing. ISBN 3-900051-07-0, URL http://www.R-project.org

Further Reading

  1. For more about R software, see R Development Core Team (2008) and visit https://www.r-project.org/

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Murugan Anandarajan
    • 1
  • Chelsey Hill
    • 2
  • Thomas Nolan
    • 3
  1. 1.LeBow College of BusinessDrexel UniversityPhiladelphiaUSA
  2. 2.Feliciano School of BusinessMontclair State UniversityMontclairUSA
  3. 3.Mercury Data ScienceHoustonUSA

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