Sentiment Analysis Approaches and Applications: A Survey

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2018
Authors:
Shamsa Umar, Maryam, Fizza Azhar, Sayyam Malik, Ghulam Samdani
10.5120/ijca2018916630

Shamsa Umar, Maryam, Fizza Azhar, Sayyam Malik and Ghulam Samdani. Sentiment Analysis Approaches and Applications: A Survey. International Journal of Computer Applications 181(1):1-9, July 2018. BibTeX

@article{10.5120/ijca2018916630,
	author = {Shamsa Umar and Maryam and Fizza Azhar and Sayyam Malik and Ghulam Samdani},
	title = {Sentiment Analysis Approaches and Applications: A Survey},
	journal = {International Journal of Computer Applications},
	issue_date = {July 2018},
	volume = {181},
	number = {1},
	month = {Jul},
	year = {2018},
	issn = {0975-8887},
	pages = {1-9},
	numpages = {9},
	url = {http://www.ijcaonline.org/archives/volume181/number1/29677-2018916630},
	doi = {10.5120/ijca2018916630},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

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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Keywords

Sentiment Analysis