Feature extraction and classification of movie reviews

Nhamo Mtetwa, Awukam Ojang Awukam, Mehdi Yousefi

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Abstract

Sentiment analysis identifies a user’s attitude towards a service, a topic or an event and it is very useful for companies that receive many written reviews of their services.We investigate the effect of feature extraction techniques on supervised machine learning classifiers using four different performance metrics using a publicly available movie review dataset. Our objective is to explore different classification algorithms as well as utilizing diverse feature extractors and compare outcomes and finally select the trio of feature extraction technique, classification algorithm and performance metric with the best result for the movie review classification use case.
Original languageEnglish
Title of host publication2018 5th International Conference on Soft Computing & Machine Intelligence (ISCMI)
PublisherIEEE
Pages67-71
Number of pages5
ISBN (Electronic)9781728113012
DOIs
Publication statusPublished - 2 May 2019

Publication series

Name
ISSN (Electronic)2640-0146

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Keywords

  • feature extraction
  • machine learning
  • sentiment analysis
  • Support Vector Machine (SVM)
  • random forest

Cite this

Mtetwa, N., Awukam, A. O., & Yousefi, M. (2019). Feature extraction and classification of movie reviews. In 2018 5th International Conference on Soft Computing & Machine Intelligence (ISCMI) (pp. 67-71). IEEE. https://doi.org/10.1109/ISCMI.2018.8703235