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

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.

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Publication Details

Published
2024-09-12
DOI
https://doi.org/10.1109/sparc61891.2024.10829097
Primary Topic
Spam and Phishing Detection
Type
article
Field-Weighted Citation Impact
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article

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

Rajeev Arora, Anoop Kumar, Dheerendra Panwar, Arpita Soni
Spam and Phishing Detection
article

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

Rajeev Arora, Anoop Kumar, Dheerendra Panwar, Arpita Soni
article en

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.

Film Independent (US), Miami Children's Hospital (US)
Industry, innovation and infrastructure
Openalex Percentile: Top 60%
Spam and Phishing Detection
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