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Prediction of Violent Extremism from Online Textual Contents

Varuna. T.V1

Section:Research Paper, Product Type: Journal Paper
Volume-06 , Issue-06 , Page no. 103-106, Jul-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6si6.103106

Online published on Jul 31, 2018

Copyright © Varuna. T.V . 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: Varuna. T.V , “Prediction of Violent Extremism from Online Textual Contents,” International Journal of Computer Sciences and Engineering, Vol.06, Issue.06, pp.103-106, 2018.

MLA Style Citation: Varuna. T.V "Prediction of Violent Extremism from Online Textual Contents." International Journal of Computer Sciences and Engineering 06.06 (2018): 103-106.

APA Style Citation: Varuna. T.V , (2018). Prediction of Violent Extremism from Online Textual Contents. International Journal of Computer Sciences and Engineering, 06(06), 103-106.

BibTex Style Citation:
@article{T.V_2018,
author = {Varuna. T.V },
title = {Prediction of Violent Extremism from Online Textual Contents},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {7 2018},
volume = {06},
Issue = {06},
month = {7},
year = {2018},
issn = {2347-2693},
pages = {103-106},
url = {https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=454},
doi = {https://doi.org/10.26438/ijcse/v6i6.103106}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i6.103106}
UR - https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=454
TI - Prediction of Violent Extremism from Online Textual Contents
T2 - International Journal of Computer Sciences and Engineering
AU - Varuna. T.V
PY - 2018
DA - 2018/07/31
PB - IJCSE, Indore, INDIA
SP - 103-106
IS - 06
VL - 06
SN - 2347-2693
ER -

           

Abstract

Social media plays a central role in society nowadays. Extremism is also a hot topic of discussion. Violent extremist activities causes major issues. It is difficult to identify people engaging in extremist activities thorough public cyber spaces like internet cafes, institutions etc... With the help of machine learning concepts the proposed system tries to analyze the online text content and classify it in to Violent or Nonviolent content. SVM Classifier is used here. Then analyzing the user activities till now it will predict the user status, which helps to detect the extremists. The proposed system helps to detect the extremism contents and extremists as well as the extremism supporting users

Key-Words / Index Term

SVM,Extremism,Violentextremism,Violent,Nonviolent

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