Product reputation model : an opinion mining based approach

Abdel-Hafez, Ahmad, Xu, Yue, & Tjondronegoro, Dian W. (2012) Product reputation model : an opinion mining based approach. In Gaber, Mohamed Medhat, Cocea, Mihaela, Weibelzahl, Stephan, Menasalvas, Ernestina, & Labbé , Cyril (Eds.) Proceedings of the 1st International Workshop on Sentiment Discovery from Affective Data (SDAD 2012), CEUR Workshop Proceedings, Bristol, pp. 16-27.

View at publisher

Abstract

Product rating systems are very popular on the web, and users are increasingly depending on the overall product ratings provided by websites to make purchase decisions or to compare various products. Currently most of these systems directly depend on users’ ratings and aggregate the ratings using simple aggregating methods such as mean or median [1]. In fact, many websites also allow users to express their opinions in the form of textual product reviews. In this paper, we propose a new product reputation model that uses opinion mining techniques in order to extract sentiments about product’s features, and then provide a method to generate a more realistic reputation value for every feature of the product and the product itself. We considered the strength of the opinion rather than its orientation only. We do not treat all product features equally when we calculate the overall product reputation, as some features are more important to customers than others, and consequently have more impact on customers buying decisions. Our method provides helpful details about the product features for customers rather than only representing reputation as a number only.

Impact and interest:

0 citations in Scopus
Search Google Scholar™

Citation counts are sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

ID Code: 58118
Item Type: Conference Paper
Refereed: Yes
Keywords: Reputation model, Opinion mining, Features impact, Opinion strength
ISSN: 1613-0073
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > Schools > School of Information Systems
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright © 2012 for the individual papers by the papers' authors. Copying permitted only for private and academic purposes. This volume is published and copyrighted by its editors.
Deposited On: 13 Mar 2013 01:25
Last Modified: 12 Jun 2013 15:36

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page