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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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Issue: May 2024
Volume 9 | Issue 5
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| Paper Title: | Cognitive Method to Detect Toxic Comments In Social Media |
| Authors Name: | Jomy Joseph , Sneha Rose , M.Jayakumar |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJNRD_215716
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| Published Paper Id: | IJNRD2403307 |
| Published In: | Volume 9 Issue 3, March-2024 |
| DOI: | |
| Abstract: | Social media is considered the most important activity that helps to consume more experience and knowledge. This is due to the massive increase in internet users worldwide, which continues to increase from millions to billions using the Internet in the operation of social media. Due to these, it has become the first information that the user consumes after waking up and before sleeping. It helps in the fulfilment of small moments of our day-today lives. Toxicity in online comments has become a major concern in today’s digital world, and detecting such comments automatically can greatly improve the safety and quality of online discussions. The project is developed in order to produce a model which can detect toxic comments with the use of Hybrid Neural Network (HNN), which is a combination of Convolutional Neural Network (CNN) and Recurrent Neutral Network (RNN). The results indicates that the use of Hybrid Neural Network has resulted in an increased efficiency in detecting toxic comments. This project mainly focuses on creating a model that can detect and control various toxics such as threats, obscenities, insults and identity-based hatred in an automated manner. This model can be further incorporated in web applications, social media, blogs, etc. |
| Keywords: | Toxic Comment, Natural Language Processing |
| Cite Article: | "Cognitive Method to Detect Toxic Comments In Social Media", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.9, Issue 3, page no.d52-d57, March-2024, Available :http://www.ijnrd.org/papers/IJNRD2403307.pdf |
| Downloads: | 00032 |
| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID:IJNRD2403307 Registration ID: 215716 Published In: Volume 9 Issue 3, March-2024 DOI (Digital Object Identifier): Page No: d52-d57 Country: Kottayam, Kerala, India Research Area: Other Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2403307 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2403307 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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