Intelligent Opinion Polarity and Analysis in Discovering Product Related Customer Reviews: A Survey

Authors

  • Sahay K Department of CSE, Truba Institute of Engineering & Technology, Bhopal, M.P., India
  • Singh K Department of CSE, Truba Institute of Engineering & Technology, Bhopal, M.P., India
  • Saxena A Department of CSE, Truba Institute of Engineering & Technology, Bhopal, M.P., India

DOI:

https://doi.org/10.26438/ijcse/v7i6.11391143

Keywords:

Sentiment analysis, Opinion mining, Machine learning, Social Media, Support Vector Machine, Sentiment Polarity

Abstract

Due to rapid advancements in Social media consumer interactions are increasing at faster rate. Twitter has now a days become a social media platform for industries, individuals, educational institutes and organizations who have a strong educational, political, industrial, social, banking or economic concern in maintaining and enhancing their social status and reputation. Posts are generally composed of poorly structured, incomplete, and noisy sentences, irregular expressions, non-dictionary terms, and ill-formed words. The problem is some customers given rating contrast with their comments. The other reviewers must read many comments and comprehend the comments that are different from the rating. Opinion Mining is the computational detailed investigation of people’s attitudes, opinions, and emotions concerning of issues, events, topics or individuals. This paper represents the survey of customer feelings related to online product with their opinion polarity and analysis.

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Published

2019-06-30
CITATION
DOI: 10.26438/ijcse/v7i6.11391143
Published: 2019-06-30

How to Cite

[1]
K. Sahay, K. Singh, and A. Saxena, “Intelligent Opinion Polarity and Analysis in Discovering Product Related Customer Reviews: A Survey”, Int. J. Comp. Sci. Eng., vol. 7, no. 6, pp. 1139–1143, Jun. 2019.

Issue

Vol. 7 No. 6 (2019): IJCSE June Edition

Section

Survey Article

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