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Evaluation of the Delta TF-IDF Features for Sentiment Analysis

  • Andrew B. SamoylovEmail author
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 436)

Abstract

This paper proposes a feature model different from bag-of-word models to analyze the sentiment of the text. The main idea of the method is improving the quality of prediction by combining a rule-based approach and the standard bag-of-words model. Results of the experiments with changing the subject, the size of reviews in data are shown. The hypothesis stating that it is better to use short message with the length of 1–2 sentences or tweets for calculation Delta TFIDF was tested.

Keywords

Sentiment analysis Tweets Subjective an objective sentences Delta TFIDF 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Southern Federal UniversityRostov-on-DonRussia

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