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Different Approaches of Sentiment Analysis

Supriya B. Moralwar1 , Sachin N. Deshmukh2

Section:Review Paper, Product Type: Journal Paper
Volume-3 , Issue-3 , Page no. 160-165, Mar-2015

Online published on Mar 31, 2015

Copyright © Supriya B. Moralwar , Sachin N. Deshmukh . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Supriya B. Moralwar , Sachin N. Deshmukh, “Different Approaches of Sentiment Analysis,” International Journal of Computer Sciences and Engineering, Vol.3, Issue.3, pp.160-165, 2015.

MLA Style Citation: Supriya B. Moralwar , Sachin N. Deshmukh "Different Approaches of Sentiment Analysis." International Journal of Computer Sciences and Engineering 3.3 (2015): 160-165.

APA Style Citation: Supriya B. Moralwar , Sachin N. Deshmukh, (2015). Different Approaches of Sentiment Analysis. International Journal of Computer Sciences and Engineering, 3(3), 160-165.

BibTex Style Citation:
@article{Moralwar_2015,
author = {Supriya B. Moralwar , Sachin N. Deshmukh},
title = {Different Approaches of Sentiment Analysis},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {3 2015},
volume = {3},
Issue = {3},
month = {3},
year = {2015},
issn = {2347-2693},
pages = {160-165},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=441},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=441
TI - Different Approaches of Sentiment Analysis
T2 - International Journal of Computer Sciences and Engineering
AU - Supriya B. Moralwar , Sachin N. Deshmukh
PY - 2015
DA - 2015/03/31
PB - IJCSE, Indore, INDIA
SP - 160-165
IS - 3
VL - 3
SN - 2347-2693
ER -

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Abstract

Sentiment analysis is a machine learning approach in which machines analyzes and classifies the sentiments, emotions, opinions about any particular topics or entity which are expressed in the form of text or speech. Due to large volume of textual data increasing on the web so much of the current research is focusing on the area of sentiment analysis. People are interested to develop and design a system that can identify and classify the sentiments as represented in textual form. Sentiment analysis is used to extract the subjective information in source material by applying various techniques such as Natural language Processing (NLP), Computational Linguistics and text analysis and classify the polarity of the opinion. In this paper, we are going to discuss different levels of sentiment analysis, approaches for sentiment classification, Data Source for sentiment analysis and comparative study of approaches for sentiment classification.

Key-Words / Index Term

Sentiment Analysis, Opinion Extraction, Text Mining, Natural Language Processing, Subjective Analysis, Machine Learning Algorithm

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