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An Empirical Analysis of Articles on Sentiment Analysis

  • Vishal Vyas
  • V. Uma
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 710)

Abstract

Expression of a thought is not only important for an individual but there is a necessity for an automated system to get an opinion from it. Sentiment analysis (SA) or opinion mining (OM) is used to identify the sentiment/opinion of the speaker. Web 2.0 provides us various platforms such as Twitter, Facebook where we comment or post to express our happiness, anger, disbelief, sadness, etc. For SA of text, computationally it is required to know the concepts and technologies being used in the field of SA. This article gives brief knowledge about the techniques used in SA by categorizing various articles over the past four years. This article also explains the preprocessing steps, various application programmable interface (API), and available datasets for a better understanding of SA. This article is concluded with a future work which needs a separate attention of researchers to improve the performance of sentiment analysis.

Keywords

Text mining Sentiment analysis Ontology Machine learning 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Department of Computer SciencePondicherry UniversityPuducherryIndia

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