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This is a Human Clinical Trial study.

September 5, 2025

Social Media Sentiment Analyzer

AMAbbas MohammedPrime Minister's Office KMKhaja Mahabubullah

Key Points

The sentiment analysis tool classifies opinions as positive, negative, or neutral in real-time.
It utilizes machine learning techniques such as Logistic Regression and Random Forest for accurate classification.
The system employs natural language processing and TF-IDF for feature extraction to enhance analysis.
Interactive dashboards help visualize results, supporting users in monitoring sentiment trends effectively.

Abstract

The Social Media Sentiment Analyzer is a real-time web-based tool designed to assess public opinions across social media platforms. Built using Python and Streamlit, the system employs natural language processing (NLP) and machine learning algorithms including Logistic Regression, Random Forest, and Neural Networks. It performs sentiment classification into positive, negative, and neutral classes using TF-IDF feature extraction. The tool provides interactive dashboards for real-time visualization and helps individuals and businesses monitor sentiment trends effectively. The system is scalable, customizable, and open-source, with support for integration into existing data workflows and potential for multilingual adaptation

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