Title :
Hybrid filtering for opinion mining
Author :
Archana Gupta;Ajita Verma;Parul Kalra
Author_Institution :
Department of I.T, ASET, Amity University, Noida, India
fDate :
4/1/2015 12:00:00 AM
Abstract :
The growth in involvement of social media with current business world has influenced online customers by unbalanced opinions about the product and services. The main objective of this paper is to standardize the opinion given by the masses about any product or services in various social media communities. Enormous opinions on a specific product or service is available due to vast exposure available for publicly voice their opinion through social media. There are enormous customer reviews available about various products and services which are not systematically arranged. Moreover, there is no proper mechanism to identify the reliable or genuine reviews. This motivates the organizations and researchers to create tools which can automatically analyze and systematically arrange only those opinions that are genuine and filter out the fake reviews. The principal focus is to frame a filtering model with the help of truth test. Every source needs to undergo through a truth test, if the source is genuine, then the opinion is concluded while making a decision else it is marked as a fake review and hence filtered from the system.
Keywords :
"Reliability","Feature extraction","Filtering","Media","Sentiment analysis","Organizations","Data mining"
Conference_Titel :
Communication Technologies (GCCT), 2015 Global Conference on
DOI :
10.1109/GCCT.2015.7342699