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22 April 2024
Reseach Article

Using BERT for Checking the Polarity of Movie Reviews

by Saad Abdul Rauf, Yan Qiang, Syed Basit Ali, Waqas Ahmad
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 177 - Number 21
Year of Publication: 2019
Authors: Saad Abdul Rauf, Yan Qiang, Syed Basit Ali, Waqas Ahmad
10.5120/ijca2019919675

Saad Abdul Rauf, Yan Qiang, Syed Basit Ali, Waqas Ahmad . Using BERT for Checking the Polarity of Movie Reviews. International Journal of Computer Applications. 177, 21 ( Dec 2019), 37-41. DOI=10.5120/ijca2019919675

@article{ 10.5120/ijca2019919675,
author = { Saad Abdul Rauf, Yan Qiang, Syed Basit Ali, Waqas Ahmad },
title = { Using BERT for Checking the Polarity of Movie Reviews },
journal = { International Journal of Computer Applications },
issue_date = { Dec 2019 },
volume = { 177 },
number = { 21 },
month = { Dec },
year = { 2019 },
issn = { 0975-8887 },
pages = { 37-41 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume177/number21/31023-2019919675/ },
doi = { 10.5120/ijca2019919675 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:46:32.398438+05:30
%A Saad Abdul Rauf
%A Yan Qiang
%A Syed Basit Ali
%A Waqas Ahmad
%T Using BERT for Checking the Polarity of Movie Reviews
%J International Journal of Computer Applications
%@ 0975-8887
%V 177
%N 21
%P 37-41
%D 2019
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this era, the data of the user on social media is generating in every millisecond. The importance of data can be noted or observed as these are the reviews, emotions, and opinions of the human being in the form of text. The customer-generated data can be related to events, food, products, etc. This information is a “key to success” for those who do business or are in government and other individuals. As the data is in the form of bulk so, it is evident that to analyze a content that is generated by a user must be complicated to manage as well as it must be time-consuming. For this, we need an intelligent system that helps us to figure out whether the content is positive, negative or neutral in the form of categories. This smart system commonly named sentiment analysis (SA), opinion mining (OM), subjectivity mining, etc. Opinion mining is the systematized mining approach. Through this, we can classify, thoughts and emotions from the text, speech, and databank sources through Natural Language Processing (NLP). The actual purpose of writing this paper is to determine the idea of human emotions with the help of BERT model, where we took a dataset of IMDB movie reviews, which are generated by a users’ data. Our experimental methodology is adequate and robust, which in turn describes the quality of sentiment analysis.

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Index Terms

Computer Science
Information Sciences

Keywords

Text classification sentiment analysis natural language processing Bidirectional Encoder Representations from Transformers.