RSS News Sentiment Analysis Dashboard

This project creates a daily-updated dashboard analyzing sentiment in news articles from various broadcasters. It uses RSS feeds to collect news data, performs sentiment analysis, and visualizes the results using a Streamlit web application.

Overview

This project creates a daily-updated dashboard analyzing sentiment in news articles from various broadcasters. It uses RSS feeds to collect news data, performs sentiment analysis, and visualizes the results using a Streamlit web application.

Pipeline

Data Collection

Script: rss_datacollection_feed.py

• Fetches news articles from RSS feeds of multiple broadcasters (BBC, NYC Times, CBS News, Aljazeera, The Guardian)
• Uses requests library to fetch RSS data
• Parses XML data using xml.etree.ElementTree

Sentiment Analysis

• Utilizes VADER (Valence Aware Dictionary and sEntiment Reasoner) for sentiment scoring
• Calculates sentiment scores for both article titles and descriptions

Data Processing

• Cleans HTML tags from descriptions
• Removes duplicates
• Saves processed data to a CSV file with a date stamp

Automated Daily Updates

• Uses GitHub Actions for daily execution of the data collection script
• Workflow defined in .github/workflows/daily_data_collection.yml
• Automatically commits and pushes updated data to the repository

Visualization

Script: app.py

• Creates a Streamlit dashboard
• Visualizations include:
  • Article count by broadcaster
  • Average sentiment scores
  • Publication time distribution
  • Sentiment distribution pie charts

Deployment

• Hosted on Streamlit Cloud
• Automatically updates with the latest data

Key Features

• Daily automated data collection and analysis
• Sentiment analysis of news articles from multiple sources
• Interactive web dashboard for data exploration
• Version-controlled data storage using GitHub

Technologies Used

• Python
• Pandas for data manipulation
• VADER for sentiment analysis
• Matplotlib for creating charts
• Streamlit for web application
• GitHub Actions for automation

Setup and Running

1. Clone the repository
2. Install dependencies: pip install -r requirements.txt
3. Run data collection: python rss_datacollection_feed.py
4. Launch Streamlit app: streamlit run app.py

Data Update Process

The data is automatically updated daily through a GitHub Actions workflow. This ensures that the dashboard always displays the most recent news sentiment analysis.

Dashboard Access

The live dashboard can be accessed at: RSS News Sentiment Analysis Dashboard