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Sentiment Classification and Feature based Summarization of Movie Reviews in Mobile Environment

by Savita Harer, Sandeep Kadam
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 100 - Number 1
Year of Publication: 2014
Authors: Savita Harer, Sandeep Kadam
10.5120/17490-8008

Savita Harer, Sandeep Kadam . Sentiment Classification and Feature based Summarization of Movie Reviews in Mobile Environment. International Journal of Computer Applications. 100, 1 ( August 2014), 30-35. DOI=10.5120/17490-8008

@article{ 10.5120/17490-8008,
author = { Savita Harer, Sandeep Kadam },
title = { Sentiment Classification and Feature based Summarization of Movie Reviews in Mobile Environment },
journal = { International Journal of Computer Applications },
issue_date = { August 2014 },
volume = { 100 },
number = { 1 },
month = { August },
year = { 2014 },
issn = { 0975-8887 },
pages = { 30-35 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume100/number1/17490-8008/ },
doi = { 10.5120/17490-8008 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:28:49.197444+05:30
%A Savita Harer
%A Sandeep Kadam
%T Sentiment Classification and Feature based Summarization of Movie Reviews in Mobile Environment
%J International Journal of Computer Applications
%@ 0975-8887
%V 100
%N 1
%P 30-35
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

A new framework is designed for sentiment classification and feature based summarization system in a mobile environment. Posting online reviews has become an increasingly popular way for people to share their opinions about specific product or service with other users. It has become a common practice for web technologies to provide the venues and facilities for people to publish their reviews. Sentiment classification and feature based summarization are essential steps for the classification and summarization of movie reviews. System proposed Random forest method for sentiment classification of movie reviews. Identification of movie features and opinion words are both important for feature based summarization. System identified movie features using a novel approach called Latent Semantic Analysis (LSA) and frequency based approach. Then system identified opinion words using part-of-speech (POS) tagging method. The result of LSA is extended to LSA based filtering mechanism to reduce the size of review summary. System design focused on the sentiment classification accuracy and system response time.

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Index Terms

Computer Science
Information Sciences

Keywords

Movie reviews Sentiment Classification Summarization POS tagging.

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