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Sentiment Analysis: Approaches and Methods

Amardeep Kaur1 , Jagroop Kaur2

Section:Review Paper, Product Type: Journal Paper
Volume-6 , Issue-7 , Page no. 1285-1287, Jul-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i7.12851287

Online published on Jul 31, 2018

Copyright © Amardeep Kaur, Jagroop Kaur . 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: Amardeep Kaur, Jagroop Kaur, “Sentiment Analysis: Approaches and Methods,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.7, pp.1285-1287, 2018.

MLA Style Citation: Amardeep Kaur, Jagroop Kaur "Sentiment Analysis: Approaches and Methods." International Journal of Computer Sciences and Engineering 6.7 (2018): 1285-1287.

APA Style Citation: Amardeep Kaur, Jagroop Kaur, (2018). Sentiment Analysis: Approaches and Methods. International Journal of Computer Sciences and Engineering, 6(7), 1285-1287.

BibTex Style Citation:
@article{Kaur_2018,
author = {Amardeep Kaur, Jagroop Kaur},
title = {Sentiment Analysis: Approaches and Methods},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {7 2018},
volume = {6},
Issue = {7},
month = {7},
year = {2018},
issn = {2347-2693},
pages = {1285-1287},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=2601},
doi = {https://doi.org/10.26438/ijcse/v6i7.12851287}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i7.12851287}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=2601
TI - Sentiment Analysis: Approaches and Methods
T2 - International Journal of Computer Sciences and Engineering
AU - Amardeep Kaur, Jagroop Kaur
PY - 2018
DA - 2018/07/31
PB - IJCSE, Indore, INDIA
SP - 1285-1287
IS - 7
VL - 6
SN - 2347-2693
ER -

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Abstract

Sentiment Analysis is application that is changing the ecommerce and many other businesses around the world. It is mainly an application related with text mining and works with the integration of machine learning algorithms(ML) and deep learning algorithms. It is used to increase the business productivity and also to better the customer experience by providing meaningful data out of unstructured data. This paper explains different ways and levels to do sentiment analysis and also explains Natural Language Processing(NLP) and its different approaches. Therefore, this paper brings an overview on sentiment analysis and different techniques and approaches integrated with it.

Key-Words / Index Term

Lexicon, Machine Learning, NLP,Semantic Analysis, Keyword Spotting

References

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