• G.MANOJ KUMAR
• MURRU SOMA SRI BHAVANI SAI KRISHNA

This project presents a comparative analysis and visualization tool for evaluating the performance of various classification algorithms across social media platforms. The implementation includes five machine learning models Random Forest, Logistic Regression, K-Nearest Neighbours, Decision Tree, and Support Vector Machine whose accuracy metrics are evaluated across five platforms: MSG, LinkedIn, Facebook, Instagram, and Twitter. Using Python's matplotlib and an interactive Streamlit application, the tool allows users to visually compare model accuracy via dynamically generated bar charts. The integration of data visualization with user interactivity enhances interpretability, providing an intuitive interface for model performance comparison.

Machine Learning, Classification Algorithms, Model Accuracy, Social Media Platforms, Data Visualization, Streamlit, Random Forest, SVM, Interactive Dashboard, Platform-wise Analysis.

"A COMPARATIVE STUDY OF SPAM FILTERING MECHANISMS IN SOCIAL PLATFORMS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 7, page no.g255-g263, July-2025, Available :http://www.jetir.org/papers/JETIR2507637.pdf

"A COMPARATIVE STUDY OF SPAM FILTERING MECHANISMS IN SOCIAL PLATFORMS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 7, page no. ppg255-g263, July-2025, Available at : http://www.jetir.org/papers/JETIR2507637.pdf