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A Sentiment Analysis of Food Review using Logistic Regression

Author

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  • Mayur Wankhade
  • A Chandra Sekhara Rao
  • Suresh Dara
  • Baijnath Kaushik

Abstract

Sentiment analysis of review is most popular task in text classification. Online or Offline user opinion about the product is great platform to collecting the large volume of data for sentiment analysis.so the overall user reviews about product are the task for sentimental analysis .it can categories into two parts positive and negative. We can train the data model and find the sentiment hidden in the review .provide the review either positive or negative by analyzing the performance with respective parameter accuracy, precision, recall and f-measure calculating for each of the algorithm for comparison. Text classification by using machine learning technique several models Perceptron, Naïve Bayes and Logistic regression used to compare the model. Among the different classification algorithm using logistic regression method accuracy level improved .Sentiment analysis is performs by using two different text feature selection method and three classification method . Problem statement here is analyzing the sentiment analysis over large dataset.

Suggested Citation

  • Mayur Wankhade & A Chandra Sekhara Rao & Suresh Dara & Baijnath Kaushik, 2017. "A Sentiment Analysis of Food Review using Logistic Regression," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 2(7), pages 251-260, September.
    • Handle: RePEc:jbh:ijsrcs:v2:y2017:i7:id:hcseit174430
    Note: Article URL: https://ijsrcseit.com/CSEIT174430
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