Toxic Content Detection in Online Social Networks: A New Dataset from Brazilian Reddit Communities
Abstract
The proliferation of online social interactions in recent years, with the consequent growth in user-generated content, has brought the escalating issue of toxic language. While automatic machine learning models have been effective in moderating the vast amount of data on online social networks, low-resource languages, such as Brazilian Portuguese, still lack efficient automated moderation tools. We address this gap by creating a novel dataset collected from some of the most popular Brazilian Reddit communities. To that end, we manually labeled a sample dataset of 2,500 comments extracted from the most engaging communities. We conducted an in-depth exploratory analysis to gain valuable insights into the language of toxic and non-toxic content. Our results show a high level of agreement among annotators, attesting to the suitability of this dataset for various downstream machine learning tasks. This research offers a significant contribution to the creation of a safer online environment for users engaging in discussions in Portuguese and paves the way for more effective automatic moderation tools using machine learning.
Copyright (c) 2024 Luiz Henrique Quevedo Lima Luiz; Ana Clara Souza Pagano Ana Clara; Adriana Silvina Pagano Adriana, Ana Paula Couto da Silva Ana
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