Detection of Cyberhectoring on Instagram
4 Pages Posted: 29 Mar 2019
Date Written: March 29, 2019
Cyberhectoring is a growing problem affecting more than half of the population. Cyberhectoring is affecting mostly among teenagers. This problem has to be tackled which is been done by many researchers. The main goal of this is to understand and automatically detect the incidents of cyberhectoring. This paper focuses on collecting data sets of Instagram i.e. images and their associated comments. A detailed analysis of the labelled data, including a study of relationships between cyberbullying and a host of features such as profanity, temporal commenting behavior, linguistic content and image content is made. The collected data is then processed and classified using classification algorithms and is further classified into bullying and non bullying content. Using the labelled data, we further design and evaluate the performance of classifiers to automatically detect incidents if cyberhectoring.
Keywords: Cyberhectoring, Cyberbullying, Automated detection, Machine Learning, CNN
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