Detection and Classification of Online Toxic Comments

Abstract

In the current century, social media has created many job opportunities and has become a unique place for people to freely express their opinions. But as every coin has two sides, the good and the bad, along with the pros, social media has many cons. Among these users, a few bunches of users are taking advantage of this system and are misusing this opportunity to express their toxic mindset (i.e., insulting, verbal sexual harassment, foul behavior, etc.). And hence cyberbullying has become a major problem. If we can filter out the hurtful, toxic words expressed on social media platforms like Twitter, Instagram, and Facebook, the online world will become a safer and more harmonious place. We gained initial ideas by researching current toxic comments classifiers to come up with this design. We then took what we found and made the most user-friendly product possible. For this project, we created a Toxic Comments Classifier which will classify the comments depending on the category of toxicity and will display the percentage of probability for each category of toxicity.