Title: Fuzzy logic-based framework for measuring strength of sentiments in web data

Authors: Anil Kumar

Addresses: CSE Department, Birla Institute of Technology, Mesra, Ranchi, India

Abstract: The users of internet are growing exponentially providing a platform to the users where they can share ideas, their experiences or feedback regarding any product, services or any event. Nowadays, social media like Facebook, Twitter, blogs, micro-blog and others are very popular medium among the users for informal discussion or feedback. Some studies show that for effective decision making informal reviews, feedback or discussion should be considered. Sentiment may be positive or negative. As previous researches shows that there are two types of emotions positive or negative which can be measured by noting or counting of some words like 'not', 'no', 'bad', 'good', etc., in their conversation text. But the set of these words having crisp set characteristics or mere occurrences of these words do not explain the degree of sentiments. Therefore, this study develops an approach to measure the degree of sentiment of web data using fuzzy logic on the basis of membership value of linguistic hedges (e.i. very, mostly, small, highly etc.) in fuzzy set. This approach provides granularity of sentiments which is very useful for effective and reliable decision making process.

Keywords: sentiment analysis; opinion mining; linguistic hedges; fuzzy logic; natural language processing; NLP.

DOI: 10.1504/IJKEDM.2017.091022

International Journal of Knowledge Engineering and Data Mining, 2017 Vol.4 No.3/4, pp.277 - 296

Available online: 03 Apr 2018 *

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