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An approach to analyze suicidal tendency in blogs and tweets using Sentiment Analysis

Shrija Madhu1

Section:Research Paper, Product Type: Isroset-Journal
Vol.6 , Issue.4 , pp.34-36, Aug-2018


CrossRef-DOI:   https://doi.org/10.26438/ijsrcse/v6i4.3436


Online published on Aug 31, 2018


Copyright © Shrija Madhu . 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: Shrija Madhu, “An approach to analyze suicidal tendency in blogs and tweets using Sentiment Analysis,” International Journal of Scientific Research in Computer Science and Engineering, Vol.6, Issue.4, pp.34-36, 2018.

MLA Style Citation: Shrija Madhu "An approach to analyze suicidal tendency in blogs and tweets using Sentiment Analysis." International Journal of Scientific Research in Computer Science and Engineering 6.4 (2018): 34-36.

APA Style Citation: Shrija Madhu, (2018). An approach to analyze suicidal tendency in blogs and tweets using Sentiment Analysis. International Journal of Scientific Research in Computer Science and Engineering, 6(4), 34-36.

BibTex Style Citation:
@article{Madhu_2018,
author = {Shrija Madhu},
title = {An approach to analyze suicidal tendency in blogs and tweets using Sentiment Analysis},
journal = {International Journal of Scientific Research in Computer Science and Engineering},
issue_date = {8 2018},
volume = {6},
Issue = {4},
month = {8},
year = {2018},
issn = {2347-2693},
pages = {34-36},
url = {https://www.isroset.org/journal/IJSRCSE/full_paper_view.php?paper_id=801},
doi = {https://doi.org/10.26438/ijcse/v6i4.3436}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i4.3436}
UR - https://www.isroset.org/journal/IJSRCSE/full_paper_view.php?paper_id=801
TI - An approach to analyze suicidal tendency in blogs and tweets using Sentiment Analysis
T2 - International Journal of Scientific Research in Computer Science and Engineering
AU - Shrija Madhu
PY - 2018
DA - 2018/08/31
PB - IJCSE, Indore, INDIA
SP - 34-36
IS - 4
VL - 6
SN - 2347-2693
ER -

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Abstract :
Sentiment Analysis(SA) or Opinion Mining is done to find the opinion of the users and customers to review and analyse their opinions on various products and services. It is one of the major tasks in business these days for knowing demands of customers. In this paper a sentiment analysis method for analyzing the suicidal tendencies in blogs and tweets is proposed. The proposed method uses concepts like Bag of words ,Part of Speech and Natural Language Processing for analzing the text.In life sometimes such a situation arises where the person finds himself trapped and suicide only seems to be the ultimate respite from all problems. Such a person may not share his mental condition verbally with anyone but may share it through tweets and messages. This paper is an approach to reach out a helping hand to such people by analyzing such tendencies in their messages. The proposed method uses Python Language module Textblob for performing different analysis task on the text.

Key-Words / Index Term :
Sentiment Analysis; Suicide; Textblob; blogs;tweets

References :
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[2]. Gimpel, K., Schneider, N., O’Connor, B., Das, D., Mills, D., Eisenstein, J., etal. “Part-of-speech tagging for twitter: Annotation, features, and experiments”. In Proceedings of the 49th annual meeting of the association for computational linguistics: Human language technologies: Short papers - volume 2 HLT ’11,pp. 42–47,2011
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[5]. Taboada, M., Brooke, J., Tofiloski, M., Voll, K., & Stede, M. “Lexicon-based methods for sentiment analysis”. Computational linguistics, 37, 267–307,2011.
[6]. Xia, R., & Zong, C. “Exploring the use of word relation features for sentiment classification”. In Proceedings of the 23rd international conference on computational linguistics: Posters COLING ’10,pp. 1336–1344,2010
[7]. Kharde,A.V., & Sonawane,S.S. “Sentiment Analysis of Twitter Data: A Survey of Techniques”. International Journal of Computer Applications, Volume 139 , No.11, 2016

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