Improved cyberbully detection techniques using multiple correlation coefficient from forum corpus Online publication date: Thu, 31-Jan-2019
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.
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