Extract topics from text collections using LDA (Latent Dirichlet Allocation) with keyword extraction and topic visualization.
Scanned 6/3/2026
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---
name: topic-modeler
description: Extract topics from text collections using LDA (Latent Dirichlet Allocation) with keyword extraction and topic visualization.
---
# Topic Modeler
Extract topics from text collections using LDA.
## Features
- **LDA Topic Modeling**: Latent Dirichlet Allocation
- **Topic Keywords**: Extract representative keywords per topic
- **Document Classification**: Assign documents to topics
- **Visualization**: Topic word clouds and distributions
- **Coherence Scores**: Evaluate topic quality
## CLI Usage
```bash
python topic_modeler.py --input documents.csv --column text --topics 5 --output topics.json
```
## Dependencies
- gensim>=4.3.0
- nltk>=3.8.0
- pandas>=2.0.0
- matplotlib>=3.7.0
- wordcloud>=1.9.0
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