Code for a large-scale analysis of political subcommunities on Reddit, including content, relationships with other subreddits, and distribution of attention. Based on a dataset of over 100 million posts from around 5 million users.
Identified distinct clusters and driving forces for climate related discussions on Reddit
Sentiment Analysis and visualizations on the Mueller Report
Real Time Web Page Classification application to continuously crawl domains for key details and identify if they are legitimate, understand their categorised industry, identify keywords as well as whois information, all in real time. Leveraging Python and Apache Kafka.
Word clouds from text or weighted CSV data, sized by count and priority. Runs entirely in the browser. AI-generated app, built via conversation with Claude (Anthropic).
Sentiment Analysis for Facebook pages
This repository contains a Python script that generates Word Clouds from text. The script uses matplotlib and wordcloud libraries to create and display the Word Cloud. It's customizable and easy to use. Just update the text in main.py and run the script to see your text transformed into a Word Cloud!
Fork of https://github.com/konstantint/talkofeurope-wordclouds adapted to an ACTA dataset
Talk of Europe Creative Camp #2: Significant words from the European Parliament speeches visualized as word clouds.
Workshop on web scraping and topic modeling using R
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