Generalisation of Cyberbullying Detection

September 01, 2020 ยท Declared Dead ยท ๐Ÿ› International Conference on Advances in Social Networks Analysis and Mining

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Authors Khoury Richard, Larochelle Marc-Andrรฉ arXiv ID 2009.01046 Category cs.CL: Computation & Language Cross-listed cs.LG, stat.ML Citations 8 Venue International Conference on Advances in Social Networks Analysis and Mining Last Checked 5 months ago
Abstract
Cyberbullying is a problem in today's ubiquitous online communities. Filtering it out of online conversations has proven a challenge, and efforts have led to the creation of many different datasets, all offered as resources to train classifiers. Through these datasets, we will explore the variety of definitions of cyberbullying behaviors and the impact of these differences on the portability of one classifier to another community. By analyzing the similarities between datasets, we also gain insight on the generalization power of the classifiers trained from them. A study of ensemble models combining these classifiers will help us understand how they interact with each other.
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