International Journal For Multidisciplinary Research

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Social Media Monitoring Platform: JodView

Author(s) Mr. Pranav Singh, Prof. Shobha Chaudhary, Mr. Pranav Gaur, Mr. Amit Kumar
Country India
Abstract The widespread adoption of social media has reshaped digital communication, enabling users to connect, share, and engage on a global scale. However, this rise in online interaction has also brought challenges, particularly the unchecked spread of violent and harmful content. In response, this project introduces a Social Media Content Monitoring System designed to collect and evaluate data—primarily from Twitter—to distinguish between violent and non-violent content. At its core, the system utilizes a powerful AI model, specifically the ‘bert-base-multilingual-uncased-sentiment’, known for its proficiency in understanding and analyzing multilingual text to determine sentiment.
The platform is developed using a comprehensive technology stack: Python powers data collection and machine learning operations due to its vast library support and data science capabilities; Node.js handles backend services for fast, scalable processing and API management; React delivers a dynamic and intuitive user interface; and MongoDB is used to store and manage large volumes of unstructured social media data.
The process begins with the real-time extraction of tweets via Twitter’s API, guided by relevant hashtags and keywords. Collected tweets are cleaned and processed to prepare them for sentiment analysis. The AI model then evaluates each post, classifying it based on its potential to incite or reflect violence. By offering continuous, real-time monitoring across multiple languages, the platform not only curbs the spread of harmful content but also promotes a safer, more responsible online environment.
Keywords Natural Language Processing(NLP), Bidirectional Encoder Representations from Transformers(BERT), General Data Protection Regulation(GDPR)
Published In Volume 7, Issue 3, May-June 2025
Published On 2025-05-05
DOI https://doi.org/10.36948/ijfmr.2025.v07i03.43858
Short DOI https://doi.org/g9hskp
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