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A Diagnosis System Framework for the Time-series analysis of the Terrorism attacks Worldwide

Dharanija. G1 , B. Chandana Priya2 , B. Manasa Sai3 , G.V. Vishnu Vardhan Reddy4 , Sujatha. K5

Section:Research Paper, Product Type: Journal Paper
Volume-07 , Issue-14 , Page no. 18-22, May-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7si14.1822

Online published on May 15, 2019

Copyright © Dharanija. G, B. Chandana Priya, B. Manasa Sai, G.V. Vishnu Vardhan Reddy, Sujatha. K . 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: Dharanija. G, B. Chandana Priya, B. Manasa Sai, G.V. Vishnu Vardhan Reddy, Sujatha. K, “A Diagnosis System Framework for the Time-series analysis of the Terrorism attacks Worldwide,” International Journal of Computer Sciences and Engineering, Vol.07, Issue.14, pp.18-22, 2019.

MLA Style Citation: Dharanija. G, B. Chandana Priya, B. Manasa Sai, G.V. Vishnu Vardhan Reddy, Sujatha. K "A Diagnosis System Framework for the Time-series analysis of the Terrorism attacks Worldwide." International Journal of Computer Sciences and Engineering 07.14 (2019): 18-22.

APA Style Citation: Dharanija. G, B. Chandana Priya, B. Manasa Sai, G.V. Vishnu Vardhan Reddy, Sujatha. K, (2019). A Diagnosis System Framework for the Time-series analysis of the Terrorism attacks Worldwide. International Journal of Computer Sciences and Engineering, 07(14), 18-22.

BibTex Style Citation:
@article{G_2019,
author = {Dharanija. G, B. Chandana Priya, B. Manasa Sai, G.V. Vishnu Vardhan Reddy, Sujatha. K},
title = {A Diagnosis System Framework for the Time-series analysis of the Terrorism attacks Worldwide},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {5 2019},
volume = {07},
Issue = {14},
month = {5},
year = {2019},
issn = {2347-2693},
pages = {18-22},
url = {https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=1081},
doi = {https://doi.org/10.26438/ijcse/v7i14.1822}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i14.1822}
UR - https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=1081
TI - A Diagnosis System Framework for the Time-series analysis of the Terrorism attacks Worldwide
T2 - International Journal of Computer Sciences and Engineering
AU - Dharanija. G, B. Chandana Priya, B. Manasa Sai, G.V. Vishnu Vardhan Reddy, Sujatha. K
PY - 2019
DA - 2019/05/15
PB - IJCSE, Indore, INDIA
SP - 18-22
IS - 14
VL - 07
SN - 2347-2693
ER -

           

Abstract

Social media(twitter) is easily conveyed organization for the enrolled people that may fuse content, photos, chronicles and hyperlinks. Individuals post whereabouts, opinions and information to help or against social media. The most terrified subject is terrorist strikes happening far and wide. Terrorist exploits the web-based life to consistently impart utilizing code signs or to build their backhanded proximity. The words with the hash sign related with them are broke down, get the evaluation of the twitter posts. This paper displays a methodology for sentiment analysis on terrorist related posts and to deal with the slants with their geolocations. Machine learning procedures like KNN (K-Nearest Neighbor), Random Forest are connected and the information is prepared utilizing Exploratory Data Analysis. The results are looked at and exhibited.

Key-Words / Index Term

Sentiment Analysis; Exploratory Data Analysis; KNN; Random Forest; Geolocations

References

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