Feature based opinion mining and sentiment analysis using fuzzy logic

  • B. Vamshi Krishna*
  • , Ajeet Kumar Pandey
  • , A. P. Siva Kumar
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapter

16 Citations (Scopus)

Abstract

This paper discusses a new model towards opinion mining and sentiment analysis of the text reviews posted in social media sites which are mostly in unstructured format. In recent years, web forums and social media has become an excellent platform to express or share opinions in the form of text about any product or any interested topic. These opinions are used for making decisions to choose a product or any entity. Opinion mining and sentiment analysis are related in a sense that opining mining deals with analyzing and summarizing expressed opinions whereas sentiment analysis classifies opinionated text into positive and negative. Feature extraction is a crucial problem in sentiment analysis. Model proposed in the paper utilizes machine learning techniques and fuzzy approach for opinion mining and classification of sentiment on textual reviews. The goal is to automate the process of mining attitudes, opinions and hidden emotions from text.

Original languageEnglish
Title of host publicationSpringerBriefs in Applied Sciences and Technology
PublisherSpringer Verlag
Pages79-89
Number of pages11
Edition9789811066979
DOIs
Publication statusPublished - 2018

Publication series

NameSpringerBriefs in Applied Sciences and Technology
Number9789811066979
ISSN (Print)2191-530X
ISSN (Electronic)2191-5318

All Science Journal Classification (ASJC) codes

  • Biotechnology
  • General Chemical Engineering
  • General Mathematics
  • General Materials Science
  • Energy Engineering and Power Technology
  • General Engineering

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