Private Line an IMDB YouTube Clone Using MERN |
Author(s): |
| Adarsh S , St Thomas College of Engineering and Technology, Chengannur; Abhinand P S, St Thomas College of Engineering and Technology, Chengannur; Adithya Krishnan U, St Thomas College of Engineering and Technology, Chengannur; Albee C John, St Thomas College of Engineering and Technology, Chengannur; Dr. Sunil S S, St Thomas College of Engineering and Technology, Chengannur |
Keywords: |
| MERN stack, NLP, User Centric Design |
Abstract |
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Platforms for sharing content, such as YouTube and IMDb, have completely changed how we find, watch, and distribute multimedia content. But hate speech, spam comments, biased reviews, and content filtering are common issues that these platforms deal with, and they can negatively impact user experience and platform integrity. To tackle these problems, this paper intends to develop a comprehensive platform that mimics YouTube and IMDb's capabilities while adding cutting-edge features to solve these problems. Private Line is a powerful solution for content discovery and moderation that makes use of the MERN (MongoDB, Express.js, React.js, Node.js) stack to provide a secure, welcoming, and interesting environment for users. A number of important features are included in Private Line to improve moderation and content discovery. This paper features hate speech removal which uses natural language processing (NLP) techniques to identify and remove offensive or insulting material from content that users have created. By removing malicious or irrelevant comments, machine learning of discussions. Thanks to sophisticated sentiment analysis algorithms, consumers may now read unbiased evaluations and get unbiased opinions on material. In this paper, certain techniques are used for spam comment identification, which enhances the quality Private Line represents a significant advancement in content sharing platforms, providing a comprehensive solution to common challenges faced by platforms like IMDb and YouTube. |
Other Details |
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Paper ID: IJSRDV12I30015 Published in: Volume : 12, Issue : 3 Publication Date: 01/06/2024 Page(s): 48-51 |
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