A Python tool that aggregates global internet sentiment from news headlines and Reddit posts, classifies emotions using a transformer-based AI model, and generates actionable decision signals for businesses or creators.
Unlike traditional sentiment analyzers, this project synthesizes multi-source emotional data into a daily “emotional fingerprint,” helping you understand the global mood and make informed decisions.
- Fetches top news headlines via NewsAPI
- Scrapes hot Reddit posts from
r/worldnews(or any subreddit) - Uses HuggingFace transformer model for multi-emotion classification:
- joy, fear, anger, sadness, surprise, trust, etc.
- Aggregates scores across sources into a weighted emotional snapshot
- Generates decision signals based on dominant emotions
- CLI-based, lightweight, and easily extendable
- Can be turned into daily mood tracker or automated alerts
- Python 3.10+
- Requests – for HTTP requests
- PRAW – Reddit API client
- Transformers + PyTorch – for emotion classification
- NewsAPI – for fetching headlines
- Clone the repo:
git clone https://github.com/rahimprz/Mood-Mapper.git
cd internet-mood-mapper