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Using Social Networking Data as a Location based Warning System

by Harsh Alkutkar, George Sam, Kailash Tambe, Bharati Ainapure
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 59 - Number 2
Year of Publication: 2012
Authors: Harsh Alkutkar, George Sam, Kailash Tambe, Bharati Ainapure
10.5120/9520-3924

Harsh Alkutkar, George Sam, Kailash Tambe, Bharati Ainapure . Using Social Networking Data as a Location based Warning System. International Journal of Computer Applications. 59, 2 ( December 2012), 26-29. DOI=10.5120/9520-3924

@article{ 10.5120/9520-3924,
author = { Harsh Alkutkar, George Sam, Kailash Tambe, Bharati Ainapure },
title = { Using Social Networking Data as a Location based Warning System },
journal = { International Journal of Computer Applications },
issue_date = { December 2012 },
volume = { 59 },
number = { 2 },
month = { December },
year = { 2012 },
issn = { 0975-8887 },
pages = { 26-29 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume59/number2/9520-3924/ },
doi = { 10.5120/9520-3924 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:05:02.856249+05:30
%A Harsh Alkutkar
%A George Sam
%A Kailash Tambe
%A Bharati Ainapure
%T Using Social Networking Data as a Location based Warning System
%J International Journal of Computer Applications
%@ 0975-8887
%V 59
%N 2
%P 26-29
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Twitter and Facebook are huge social networks that contain a lot of data that can be used for sentiment analysis. We often find out that a particular area we travel to is dangerous, after asking around. However what if we could use social networking data like 'tweets' to find out if a place is actually dangerous? This paper introduces how to use social networking data, analyze it and use it for alerting someone in a disaster prone or high crime rate prone area with the help of smartphones using natural language processing and sentiment analysis.

References
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  2. Akshi Kumar, Teeja Mary Sebasitan 2012, Sentiment Analysis: A Perspective on its Past, Present and Future. International Journal of Intelligent Systems and Applications
  3. Ion SMEUREANU ; Cristian BUCUR 2012, Applying Supervised Opinion Mining Techniques on Online User Reviews, Informatica Economica Journal
  4. Han Xiao Shi. A sentiment analysis model for hotel reviews based on supervised learning, Machine Learning and Cybernetics (ICMLC), 2011 International Conference.
  5. Pang Heming, Jiang Linying, Yang Liu, Yue Kun. Design and Implementation of Android Phone Surveillance System - IEEE 2010 International Forum on Information Technology and Applications
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  7. Ming Hao. Visual sentiment analysis on twitter data streams , Hewlett-Packard Labs. , Palo Alto, CA, USA - Visual Analytics Science and Technology (VAST), 2011 IEEE Conference - Conference Publications
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  10. Sentiment140 – Twitter Analysis Website http://www. sentiment140. com/
  11. Ming Hao- VAST, 2009 - Visual Opinion Analysis of Customer Feedback Data
Index Terms

Computer Science
Information Sciences

Keywords

Social Networks Data Mining Warning System Android

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