Classification of Online Toxic Comments Using Machine Learning Algorithms


Toxic comments are online remarks that are insulting, abusive, or inappropriate, and frequently cause other users to quit a debate. The threat of online bullying and harassment obstructs the free flow of ideas by limiting people's dissenting viewpoints. Sites fail to properly promote discussions, forcing many communities to limit or eliminate user comments entirely.

This article will examine the scope of online harassment and categorize the content into labels in order to assess the toxicity as accurately as feasible. We will employ six Machine Learning algorithms and apply them to our data to address the problem of text classification and to determine the best Machine Learning method for harmful comments categorization based on our evaluation metrics.

We will strive to examine toxicity with high precision in order to reduce its negative impacts, which will serve as a motivator for businesses to take the necessary steps.

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