📰 Python Google News scraper for headlines, summaries & sources. Media monitoring, trend analysis with proxy rotation & automated CSV export.
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Updated
May 13, 2025 - Python
📰 Python Google News scraper for headlines, summaries & sources. Media monitoring, trend analysis with proxy rotation & automated CSV export.
Matrix-based News Aggregation to Explore Media Bias
A Dashboard which can be utilised by the Financial Analysts to analyse the market trends and news.
An auto-refreshing dataset of major news domains and their X (formerly Twitter) accounts, complete with real-time stats like follower counts and engagement metrics. Made for tracking media trends and analytics at scale.
A fully automated data pipeline that ingests financial news from Finnhub API, stores it in MongoDB Atlas, performs sentiment analysis, and loads results into PostgreSQL — orchestrated using Apache Airflow.
Tool for detecting bias towards entity/people in the news and highlight that to the reader in the form an attractive visualization
RESTful News Analytics Platform
Inspired by *Managing real-time risks and returns: The Thomson Reuters NewsScope Event Indices*
ProMedia Insight Hub is an AI-powered media analytics dashboard for managing, analyzing, and extracting strategic insights from news data in a modern and efficient way.
This project documents the development of a Python-based Forex trading algorithm that integrates technical indicators and news analytics to automate trading strategies on MetaTrader 5.
Smart Article Summarizer is a lightweight AI-powered web app that extracts and summarizes the content of any article from the internet. It uses newspaper3k for article parsing and a Large Language Model (LLM) via LangChain and OpenAI to generate concise summaries in natural language.
🌀 Recursive Currents is a data-driven exploration of global news, clustering 50,000+ articles by shared named entities (people, places, organizations). It reveals how world narratives connect—across borders, topics, and timelines—through the names that keep appearing together. Built with Python, scikit-learn, and Plotly.
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