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Reseach Article

Sentiment Analysis Approaches and Applications: A Survey

by Shamsa Umar, Maryam, Fizza Azhar, Sayyam Malik, Ghulam Samdani
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 181 - Number 1
Year of Publication: 2018
Authors: Shamsa Umar, Maryam, Fizza Azhar, Sayyam Malik, Ghulam Samdani

Shamsa Umar, Maryam, Fizza Azhar, Sayyam Malik, Ghulam Samdani . Sentiment Analysis Approaches and Applications: A Survey. International Journal of Computer Applications. 181, 1 ( Jul 2018), 1-9. DOI=10.5120/ijca2018916630

@article{ 10.5120/ijca2018916630,
author = { Shamsa Umar, Maryam, Fizza Azhar, Sayyam Malik, Ghulam Samdani },
title = { Sentiment Analysis Approaches and Applications: A Survey },
journal = { International Journal of Computer Applications },
issue_date = { Jul 2018 },
volume = { 181 },
number = { 1 },
month = { Jul },
year = { 2018 },
issn = { 0975-8887 },
pages = { 1-9 },
numpages = {9},
url = { },
doi = { 10.5120/ijca2018916630 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-07T01:04:59.266838+05:30
%A Shamsa Umar
%A Maryam
%A Fizza Azhar
%A Sayyam Malik
%A Ghulam Samdani
%T Sentiment Analysis Approaches and Applications: A Survey
%J International Journal of Computer Applications
%@ 0975-8887
%V 181
%N 1
%P 1-9
%D 2018
%I Foundation of Computer Science (FCS), NY, USA

Nowadays utilization of social communication sites are developing various types and nature`s of client are being use this benefits often times. Peoples on social media share their views, opinions and emotions symbolically or in text form. This situation and trend attract attention towards the research of sentiment analysis. Therefore, sentiment investigation idea is proposed. Among various applications of Natural Language processing (NLP) and Machine Learning (ML) Sentiment Analysis (SA) is very popular. The vital task of sentiment analysis is classification of sentiments, by automatically classifying the opinions/reviews and sentiments into three classes positive, negative and neutral. Many classification researches are conducted over the years to know the exact feelings and situations of sentimental emotions of peoples. Classification, fuzzy and clustering is used. Fuzzy based classification is finding more accurate. Furthermore the classical text classification models are utilized for comparative execution study. The comparative performance study shows the viability of the proposed order method and capable to deliver the more precise outcomes when contrasted with conventional classifiers. In this paper we have discussed different researcher’s work on sentimental analysis approach and classification. This paper also presents the importance of opinion mining and sentiment analysis.

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Index Terms

Computer Science
Information Sciences


Sentiment Analysis