Automatic Multi Model Cyber Bullying Detection from Social Networks

7 Pages Posted: 22 Feb 2018

See all articles by T Pradheep

T Pradheep

Pondicherry Engineering College - Department of Computer Science and Engineering, Students

J.I Sheeba

Pondicherry Engineering College

T Yogeshwaran

Pondicherry Engineering College - Department of Information Technology, Students

S Pradeep Devaneyan

Christ College of Engineering and Technology

Date Written: December 2017

Abstract

Cyberbullying has grown as an important societal challenge nowadays. The Cyberbullying affects both in terms of psychological and emotional means of a person. So there is a need to devise a method to detect and prevent cyberbullying in social networks. Most of the existing cyberbullying methods involves only text detection and few methods are available for analysing the visual detection. In this proposed work is going to detect multimodel cyberbullying such as audio, video, image along with text in the social networks. The cyberbully image will be detected using the computer vision algorithm which includes two methods like Image Similarity and Optical Character Recognition (OCR). The cyberbully video will be detected using the Shot Boundary detection algorithm where the video will be broken into frames and analysed using various methods in it. The proposed framework also support to identify the cyberbully audio in the social network. Finally the cyberbully data will be classified into Physical bullying, Social bullying and Verbal bullying using classifiers.

Keywords: Cyberbully Detection, Social Networks, Physical bullying, Social bullying, Verbal bullying, Classifiers

Suggested Citation

Pradheep, T and Sheeba, J.I and Yogeshwaran, T and Pradeep Devaneyan, S, Automatic Multi Model Cyber Bullying Detection from Social Networks (December 2017). Proceedings of the International Conference on Intelligent Computing Systems (ICICS 2017 – Dec 15th - 16th 2017) organized by Sona College of Technology, Salem, Tamilnadu, India, Available at SSRN: https://ssrn.com/abstract=3123710 or http://dx.doi.org/10.2139/ssrn.3123710

T Pradheep (Contact Author)

Pondicherry Engineering College - Department of Computer Science and Engineering, Students ( email )

India

J.I Sheeba

Pondicherry Engineering College ( email )

Pondicherry
India

T Yogeshwaran

Pondicherry Engineering College - Department of Information Technology, Students ( email )

India

S Pradeep Devaneyan

Christ College of Engineering and Technology ( email )

Pitchaveeranpet
Moolakulam
Puducherry, 605 010
India

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