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Detection of Online Toxic Comments Using Deep Learning

EasyChair Preprint no. 8512

6 pagesDate: July 20, 2022


Toxic comments are disrespectful, abusive. Unreasonable online comments that usually make other users leave a discussion. The danger of online bullying and harassment affects the free flow of thoughts by restricting the dissenting opinions of people. Sites struggle to promote discussions effectively, leading many communities to limit or close down user comments altogether. We will systematically examine the extent of online harassment and classify the content into labels to examine the toxicity as correctly as possible. We will aim at examining the toxicity with high accuracy to limit down its adverse effects which will be an incentive for organizations to take the necessary steps like reporting the user or blocking the user.

Keyphrases: deep learning, machine learning, Online hate, siddharth institute, social media, toxic comment, toxicity

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {K Jagadeesh and G Himabindu and P Bhargav and B Imran and G Indiravathi},
  title = {Detection of Online Toxic Comments Using Deep Learning},
  howpublished = {EasyChair Preprint no. 8512},

  year = {EasyChair, 2022}}
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