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Reseach Article

Product Attribute Sentiment Analysis

Published on September 2018 by Raju B N, Rajahmad Jumnal, Santosh Pawar
National Conference on Computer Science and Information Technology
Foundation of Computer Science USA
NCCSIT2017 - Number 1
September 2018
Authors: Raju B N, Rajahmad Jumnal, Santosh Pawar
ef004482-a601-456a-a303-c1117a6e7a9b

Raju B N, Rajahmad Jumnal, Santosh Pawar . Product Attribute Sentiment Analysis. National Conference on Computer Science and Information Technology. NCCSIT2017, 1 (September 2018), 25-30.

@article{
author = { Raju B N, Rajahmad Jumnal, Santosh Pawar },
title = { Product Attribute Sentiment Analysis },
journal = { National Conference on Computer Science and Information Technology },
issue_date = { September 2018 },
volume = { NCCSIT2017 },
number = { 1 },
month = { September },
year = { 2018 },
issn = 0975-8887,
pages = { 25-30 },
numpages = 6,
url = { /proceedings/nccsit2017/number1/29985-7017/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference on Computer Science and Information Technology
%A Raju B N
%A Rajahmad Jumnal
%A Santosh Pawar
%T Product Attribute Sentiment Analysis
%J National Conference on Computer Science and Information Technology
%@ 0975-8887
%V NCCSIT2017
%N 1
%P 25-30
%D 2018
%I International Journal of Computer Applications
Abstract

In the digitized world today internet is tone of the main sources of the information. There are several e-commerce websites where people/customers discuss different aspects/issues of the product. All such website provides a platform for the consumers to discuss and provide their opinion about the product, its features and their services. These opinions and reviews of the consumers provide very rich information both for other users as well as firms. But the issue with this information is that the information is mostly unorganized and therefore it is difficult to create a knowledge base out of it. What this paper propose is a product facet ranking framework which automatically determines the important facets of the product from the online comments/reviews, aiming to improve the usability of the consumer reviews. The facets are identified by the following observations; 1) The important facets of a product are usually given by several consumers in the review. 2) The review/opinion of the consumer on important facet of the product influences the overall opinion or view of the consumer on the product. But identifying the most important facets will increase the usefulness of the innumerable reviews/opinions and is useful to both users and the firms itself. It is practically difficult for the people to manually identify the important facets of the products from the consumer reviews/opinions. Consumer can easily make purchasing decision by focusing more on the important features, while the firms can concentrate on improving the quality of the features or facets of the product.

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Index Terms

Computer Science
Information Sciences

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