Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Identifying and Analyzing Toxic Behavior in Ecommerce Industry through Reddit Discussions Using BERT and HateBERT

Version 1 : Received: 25 August 2024 / Approved: 26 August 2024 / Online: 26 August 2024 (08:28:03 CEST)

How to cite: KUMAR, A.; SONI, A.; Arora, R.; Panwar, D. Identifying and Analyzing Toxic Behavior in Ecommerce Industry through Reddit Discussions Using BERT and HateBERT. Preprints 2024, 2024081797. https://doi.org/10.20944/preprints202408.1797.v1 KUMAR, A.; SONI, A.; Arora, R.; Panwar, D. Identifying and Analyzing Toxic Behavior in Ecommerce Industry through Reddit Discussions Using BERT and HateBERT. Preprints 2024, 2024081797. https://doi.org/10.20944/preprints202408.1797.v1

Abstract

This study begins by looking at how toxic behaviour in video games is talked about and identified. We set up a clear idea of what “toxic behaviour" means and suggested ways to figure out when it's happening. To test these ideas, we scrape a huge collection of posts from Reddit where people talk about games. We cleaned up the data—making sure it was all good for checking. We used Bidirectional Encoder Representations from Transformers (BERT) to look at toxic behaviour. We also used HateBERT to compare how well it works at spotting toxic stuff. To make sure our models were doing a good job, we looked at over 5500 posts and decided if they were toxic or not. This helped us see if the models were right or wrong. We also used measures—to compare how much toxic stuff is in Reddit—especially for games. This helped us understand how common and different toxic behaviour is in different places.

Keywords

BERT; Games; HateBERT; Mean Behavior; Reddit

Subject

Computer Science and Mathematics, Artificial Intelligence and Machine Learning

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