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Sentiment Analysis on Twitter Data: A Study of methods based on negativity or positivity

Amit Malik1 , Ashish Yadav2 , Boby 3 , Manju More4

Section:Research Paper, Product Type: Journal Paper
Volume-07 , Issue-14 , Page no. 64-67, May-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7si14.6467

Online published on May 15, 2019

Copyright © Amit Malik, Ashish Yadav, Boby, Manju More . 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: Amit Malik, Ashish Yadav, Boby, Manju More, “Sentiment Analysis on Twitter Data: A Study of methods based on negativity or positivity,” International Journal of Computer Sciences and Engineering, Vol.07, Issue.14, pp.64-67, 2019.

MLA Style Citation: Amit Malik, Ashish Yadav, Boby, Manju More "Sentiment Analysis on Twitter Data: A Study of methods based on negativity or positivity." International Journal of Computer Sciences and Engineering 07.14 (2019): 64-67.

APA Style Citation: Amit Malik, Ashish Yadav, Boby, Manju More, (2019). Sentiment Analysis on Twitter Data: A Study of methods based on negativity or positivity. International Journal of Computer Sciences and Engineering, 07(14), 64-67.

BibTex Style Citation:
@article{Malik_2019,
author = {Amit Malik, Ashish Yadav, Boby, Manju More},
title = {Sentiment Analysis on Twitter Data: A Study of methods based on negativity or positivity},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {5 2019},
volume = {07},
Issue = {14},
month = {5},
year = {2019},
issn = {2347-2693},
pages = {64-67},
url = {https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=1091},
doi = {https://doi.org/10.26438/ijcse/v7i14.6467}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i14.6467}
UR - https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=1091
TI - Sentiment Analysis on Twitter Data: A Study of methods based on negativity or positivity
T2 - International Journal of Computer Sciences and Engineering
AU - Amit Malik, Ashish Yadav, Boby, Manju More
PY - 2019
DA - 2019/05/15
PB - IJCSE, Indore, INDIA
SP - 64-67
IS - 14
VL - 07
SN - 2347-2693
ER -

           

Abstract

This venture explanation is the issue of idea for examination in twitter that is arranging tweets according to the thought verbalized in them: positive, negative or unprejudiced. The aim of this paper is to develop a functional classifier for accurate and automatic sentiment classification of an unknown tweet stream Twitter is an online micro-blogging and social-networking platform which allows users to write short status updates. It is a rapidly developing administration with more than millions enlisted clients. Due to this large amount of usage all of us hope to achieve a reflection of public sentiment by analysing the sentiments expressed in the tweets. Analysing the public sentiment is important for many applications such as firms trying to find out the response of their products in the market, predicting political elections and predicting socio-economic phenomena like stock exchange

Key-Words / Index Term

NLP, Sentiment Analysis, Polarity, DMT, Support Vector Machine (SVM)

References

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