Identify Cyber Bulling words using Clustering for Social Media
A. Bichhwe1 , R. Khatri2
Section:Research Paper, Product Type: Journal Paper
Volume-6 ,
Issue-6 , Page no. 525-528, Jun-2018
CrossRef-DOI: https://doi.org/10.26438/ijcse/v6i6.525528
Online published on Jun 30, 2018
Copyright © A. Bichhwe, R. Khatri . 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: A. Bichhwe, R. Khatri, “Identify Cyber Bulling words using Clustering for Social Media,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.6, pp.525-528, 2018.
MLA Style Citation: A. Bichhwe, R. Khatri "Identify Cyber Bulling words using Clustering for Social Media." International Journal of Computer Sciences and Engineering 6.6 (2018): 525-528.
APA Style Citation: A. Bichhwe, R. Khatri, (2018). Identify Cyber Bulling words using Clustering for Social Media. International Journal of Computer Sciences and Engineering, 6(6), 525-528.
BibTex Style Citation:
@article{Bichhwe_2018,
author = {A. Bichhwe, R. Khatri},
title = {Identify Cyber Bulling words using Clustering for Social Media},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {6 2018},
volume = {6},
Issue = {6},
month = {6},
year = {2018},
issn = {2347-2693},
pages = {525-528},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=2216},
doi = {https://doi.org/10.26438/ijcse/v6i6.525528}
publisher = {IJCSE, Indore, INDIA},
}
RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i6.525528}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=2216
TI - Identify Cyber Bulling words using Clustering for Social Media
T2 - International Journal of Computer Sciences and Engineering
AU - A. Bichhwe, R. Khatri
PY - 2018
DA - 2018/06/30
PB - IJCSE, Indore, INDIA
SP - 525-528
IS - 6
VL - 6
SN - 2347-2693
ER -
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Abstract
Today the Internet may be a very important a part of each day’s life, and lots of information is generated. Discovering data from vast quantity of information manually may be very difficult, oft impossible. Researchers in cyber security face increasing amounts of knowledge and it`s evident that additional powerful tools area unit required to handle. Cyber bullying indirectly, direct attacks (messages sent on to their children), and cyber bullying (with or while not the victim`s information to help fellow cyber bully others) are two types. Indirectly concerned in cyber bullying, harassment adults actually because it`s too dangerous.
Key-Words / Index Term
Sentiment analysis, opinion mining, Support Vector Machine, Term Frequency, TF-IDF
References
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