An approach towards feature specific opinion mining and sentimental analysis across e-commerce websites

Author

Kumar Singh, Prashast ; Sachdeva, Anish ; Mahajan, Dhruv ; Pande, Nishtha ; Sharma, Ashok

Author_Institution

CSE Dept., MSIT, New Delhi, India

fYear

2014

fDate

25-26 Sept. 2014

Firstpage

329

Lastpage

335

Abstract

This research aims to automate the process of gathering online, end user reviews for any given product or service and analyzing those reviews in terms of the sentiments expressed about specific features. This involves the filtering of irrelevant and unhelpful reviews, quantification of the sentiments of thousands of (useful) reviews. And finally, providing the end user (business/manufacturer) summarized data about the expressed sentiments in way of intuitive and easy to understand graphs, charts and other visualization. This data can then be used to improve business outcomes and ensure a very high level of customer satisfaction.

Keywords

Web sites; customer satisfaction; data mining; data visualisation; electronic commerce; information filtering; text analysis; business outcome; charts; customer satisfaction; e-commerce Websites; end user summarized data; feature specific opinion mining; graphs; irrelevant review filtering; online end user review gathering; product review; review analysis; sentiment quantification; sentimental analysis; service review; unhelpful review filtering; visualization; Batteries; Business; Data mining; Databases; Feature extraction; Filtering; Knowledge based systems; Opinion mining; Sentiment Analysis; ecommerce; feature specific mining;

fLanguage

English

Publisher

ieee

Conference_Titel

Confluence The Next Generation Information Technology Summit (Confluence), 2014 5th International Conference -

Conference_Location

Noida

Print_ISBN

978-1-4799-4237-4

Type

conf

DOI

10.1109/CONFLUENCE.2014.6949312

Filename

6949312