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Automated Review Analyzing System Using Sentiment Analysis

Publication Type : Journal Article

Publisher : Advances in Intelligent Systems and Computing

Source : Advances in Intelligent Systems and Computing, Springer Verlag, Volume 904, p.329-338 (2019)

Url :

ISBN : 9789811359330

Keywords : Analyzing system, Behavioral research, Data mining, E-commerce websites, Electronic commerce, Human behaviors, Lexicon method, Review systems, Sentiment analysis, Stars, Various technologies, Web crawler, Web crawling, Websites, Weighing systems

Campus : Amritapuri

School : School of Arts and Sciences

Department : Physics

Year : 2019

Abstract : An integral part of human behavior has always been to find out what others think about what would happen next. With the ongoing trend of e-commerce websites and personal blogs, people make active use of various technologies to understand and classify opinions. This paper introduces a new system to understand the emotions and feelings underlying the reviews provided by users on various e-commerce websites. This system holds an edge over the current rating system of star values by providing the users with a more precise and descriptive result. The main disadvantage of the star system is that it does not provide enough choice to the user. The methodology mentioned in this paper, named ARAS or Automated Review Analyzing System, overcomes this issue by using sentiment analysis which feeds upon each word in the review rather than a separate weighing system. © 2019, Springer Nature Singapore Pte Ltd.

Cite this Research Publication : A. C. Jishag, Rakhesh, V., Mohan, S., N. Varma, V., Shabu, V., Nair, L. S., and Menon, M., “Automated Review Analyzing System Using Sentiment Analysis”, Advances in Intelligent Systems and Computing, vol. 904, pp. 329-338, 2019.

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