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INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016 open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15 |
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| Paper Title: | Toxic comment classificaton using Machine Learning |
| Authors Name: | Esarla Umesh Chandra Naidu , J Janisha , G Rajesh , G T V Satyanarayana , G Naveen Sai Manikanta |
| Unique Id: | IJSDR2404112 |
| Published In: | Volume 9 Issue 4, April-2024 |
| Abstract: | Toxic users are those that leave a debate because of insulting, violent, aggressive, or unreasonable remarks. In the modern age, social media has permeated every area of people's lives. There are several reasons why people are bullied. Some people use the internet as a means of venting their resentment, anxieties, and biases, while others would like to engage in civilized conversation. This kind of antisocial behaviour is often displayed in online debates, discussions, and skirmishes when insulting and rude remarks—also known as poisonous remarks—are exchanged. Comments containing explicit language might fall into a wide range of categories, such as Identity Hate, Obscene, Threat, Severe Toxic, and Toxic. Many give up trying to find solutions and stop expressing themselves since they fear being mistreated and harassed. |
| Keywords: | Natural Language Processing, Word Embeddings, Linear Regression , XG boost, MNBM. |
| Cite Article: | "Toxic comment classificaton using Machine Learning", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.9, Issue 4, page no.801 - 807, April-2024, Available :http://www.ijsdr.org/papers/IJSDR2404112.pdf |
| Downloads: | 000338171 |
| Publication Details: | Published Paper ID: IJSDR2404112 Registration ID:210833 Published In: Volume 9 Issue 4, April-2024 DOI (Digital Object Identifier): Page No: 801 - 807 Publisher: IJSDR | www.ijsdr.org ISSN Number: 2455-2631 |
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