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.
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Notes
- 1.
For additional information on tidytext and more examples, consult http://tidytextmining.com/
References
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.
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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
For more about R software, see R Development Core Team (2008) and visit https://www.r-project.org/
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Anandarajan, M., Hill, C., Nolan, T. (2019). Sentiment Analysis of Movie Reviews Using R. In: Practical Text Analytics. Advances in Analytics and Data Science, vol 2. Springer, Cham. https://doi.org/10.1007/978-3-319-95663-3_13
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DOI: https://doi.org/10.1007/978-3-319-95663-3_13
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