Improved cyberbully detection techniques using multiple correlation coefficient from forum corpus
by J.I. Sheeba; S. Pradeep Devaneyan; Prathyusha Tata
International Journal of Autonomic Computing (IJAC), Vol. 3, No. 2, 2018

Abstract: Today, there are many prominent online sites where people share their experiences regarding crimes and anti-social behaviour. In this regard, a major unaddressed and even unidentified problem that is experienced in the social network websites is cyberbully. This proposed framework primarily targets the cyberbullying in the crime investigation forum since a high degree of cyberbully is common in crime forums. In this paper, a highly furnished representational framework is proposed that is specific to cyberbully detection using hybrid techniques (multiple correlation coefficient - MCC and support vector machine - SVM). The bag of words are given individual weights to examine their correlations using MCC algorithm before feeding them into a linear SVM classifier that identifies and classifies the cyberbully words. The efficiency of the system developed can be enhanced by analysing the evaluation metrics and the dataset validation metrics.

Online publication date: Mon, 28-Jan-2019

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