Week 3: Stable Topics with BERTopic / Articles / dracoblue.net In Week 1 (extraction) and Week 2 (embeddings + KMeans in BigQuery ML) we laid the groundwork. This week I built a Python BERTopic stage whose IDs stay stable across runs by mapping BERTopic’s interna...

TopicWatchdog – Week 3: KMeans worked, but cluster IDs kept jumping across retrains. This week I added a Python BERTopic stage with a BigQuery registry → stable topic IDs!

Blog: dracoblue.net/dev/topicwat...

#TopicWatchdog #BERTopic #BigQuery #Clustering #MachineLearning #FediScience

Week 2: Embeddings & KMeans Clustering of Topics/Claims / Articles / dracoblue.net This post documents Week 2 of the TopicWatchdog project.Last week we successfully extracted topics and claims from German political short videos and persisted them in BigQuery.However, topics often ap...

TopicWatchdog (Week 2)

Move beyond string matching: cluster political topics from German shorts with embeddings + KMeans in BigQuery ML.

Blogpost with SQL & charts:
🔗 dracoblue.net/dev/topicwat...

#TopicWatchdog #BigQuery #Embeddings #Clustering #MachineLearning #FediScience

Kickoff (Week 1): Extracting Topics & Claims from German Politics Videos / Articles / dracoblue.net This post documents Week 1 of a research project I call TopicWatchdog: an end‑to‑end, reproducible pipeline that (a) collects German political short videos, (b) transcribes them, (c) extracts topics a...

Kickoff: TopicWatchdog (Week 1)

Collect German political shorts, transcribes them, extracts topics & claims with timestamps, and stores everything in BigQuery for transparent analysis. dracoblue.net/dev/kickoff-...

#TopicWatchdog #BigQuery #MachineLearning #LLM #OpenData #FediScience