Detecting Sentiments from Movie Reviews by Integrating Reviewers Own Prejudice

Swati Gupta; Kalpana Yadav; Sumit K. Yadav

Detecting Sentiments from Movie Reviews by Integrating Reviewers Own Prejudice

Swati Gupta * §

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Kalpana Yadav

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Sumit K. Yadav

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§ INDIRA GANDHI DELHI TECHNICAL UNIVERSITY

Detecting Sentiments from Movie Reviews by Integrating Reviewers Own Prejudice

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Abstract

Presently, sentiment analysis algorithms are widely used to extract positive or negative feedback scores of various objects on the basis of the text/reviews. But, an individual may have a certain degree of biasness towards a certain product/company and hence may not objectively review the object. We try to combat this biasness problem by incorporating the positive and negative bias component in the existing sentiment score of the object. This paper proposes several algorithms for a new system of implementing individual bias in the corpus of data i.e. movie reviews in this case. Each review comment has an unadjusted sentiment score associated with it. This unadjusted score is refined to give an adjusted score using the positive and negative bias score. The bias score is calculated using certain parameters, the weightage of which has been determined by conducting a survey. We lay emphasis on the degree of biasness an individual has towards or against the review parameters for the movie reviews corpus namely actor, director and genre. We equip the system with the capability to handle various scenarios like positive inclination of the user, negative inclination of the user, presence of both positive and negative inclination of the user and neutral attitude of the user by implementing the formulae we developed.

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Swati Gupta, Kalpana Yadav, Sumit K. Yadav. 2016. "Detecting Sentiments from Movie Reviews by Integrating Reviewers Own Prejudice". Global Journal of Computer Science and Technology - G: Interdisciplinary GJCST-G Volume 15 (GJCST Volume 15 Issue G2).

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

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Classification

I.3.3

Submission ReceivedApril 10, 2015
Peer Review Double Blind
Handling Editor
Accepted May 2, 2015
Published May 15, 2015

Version of record

v1.2

Issue date

January 7, 2016

Language

English

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Article Matrices

Total Score: 143

Country: India

Subject: Global Journal of Computer Science and Technology

Authors: Kalpana Yadav, Sumit K. Yadav, Swati Gupta (PhD/Dr. count: 0)

View Count (all-time): 424

Total Views (Real + Logic): 1615

Total Downloads (simulated): 88

Publish Date: 2015 05, Fri

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Total Views: 1.6K

Total Downloads: 88

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