Behavioral Analysis of Depressed Sentimental Over Twitter: Based on Supervised Machine Learning Approach

Proceedings of 3rd International Conference on Internet of Things and Connected Technologies (ICIoTCT), 2018 held at Malaviya National Institute of Technology, Jaipur (India) on March 26-27, 2018

7 Pages Posted: 9 May 2018

See all articles by Sandeep Bhargava

Sandeep Bhargava

Suresh Gyan Vihar University

Seema Choudhary

Suresh Gyan Vihar University

Date Written: May 9, 2018

Abstract

Microblogging is an especially prevalent broadcast medium amidst the net fraternity currently. Social networking sites and web access have become pervasive and a basic element, they have emerged as a major platform for people to share their emotions, opinions, and reviews. The essence of the social content posted, the expressed feelings hidden in the exposed content can be greatly analyzed by sentimental analysis. Consequently, the possibility and growth of cybercrime have enhanced also. To reduce these case, we propose a method during this paper “Twitter - surveillance based on supervised machine learning approach” that can discover different harmful activities, depressed sentimental content and cyber crimes like commit suicide, physical assault, the misuse of photographs or recording of a pornographic, erotic or awkward nature, abusive trolling, blackmail, spam, fraud etc. from the social network sites. Social networking sites can be preventing such activities from providing timely notifications through helpline notification. The goal of this study is to classify twitter data with more accuracy and reliableness into sentiments by exploiting different-different supervised machine learning classifiers.

Suggested Citation

Bhargava, Sandeep and Choudhary, Seema, Behavioral Analysis of Depressed Sentimental Over Twitter: Based on Supervised Machine Learning Approach (May 9, 2018). Proceedings of 3rd International Conference on Internet of Things and Connected Technologies (ICIoTCT), 2018 held at Malaviya National Institute of Technology, Jaipur (India) on March 26-27, 2018. Available at SSRN: https://ssrn.com/abstract=3175816 or http://dx.doi.org/10.2139/ssrn.3175816

Sandeep Bhargava (Contact Author)

Suresh Gyan Vihar University ( email )

Mahal
Jagatpura
Jaipur, RI Rajasthan 302017
India

Seema Choudhary

Suresh Gyan Vihar University

Mahal
Jagatpura
Jaipur, RI Rajasthan 302017
India

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