This project includes a web scraper designed to extract tweets from specified Twitter (X) user profiles using Selenium and BeautifulSoup, analyze the tweets by extracting keywords and generating summaries with a Language Model Module (LLM API), and save the results in JSON format.

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A Python-based web scraper that automates tweet collection from X.com (Formerly Twitter) using Selenium. It searches for user-defined keywords, extracts tweet content, usernames, and timestamps, and saves the results to a CSV file with support for progress saving and basic anti-bot measures.

Twitter Trend Scraper is a Flask-based web application that automates the process of extracting trending topics from Twitter. The project uses Selenium for browser automation and MongoDB for storing the extracted data.

The Twitter Scraper is a Python and Streamlit-based web app that extracts real-time tweets without using the official Twitter API. It provides live data display with just one click — no database or authentication needed. Built using Selenium and ProxyMesh, it helps users analyze trending topics, hashtags, and sentiments instantly.

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This project is a web scraper that extracts Twitter profile details and stores them in a MySQL database. It uses Selenium for web automation and MySQL for data storage.