Agent skill

topic-modeling-text-mining

Apply LDA, NMF, and other computational methods to discover patterns in large text corpora with appropriate parameter tuning

a5c.ai1,642★ · 1 repos on radarProfile →
claude-codecodexcan modify filesMIT
Install
npx skills add a5c-ai/babysitter --skill topic-modeling-text-mining --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 2 KB
Bundled scripts: none
Allowed tools: ReadGrepWriteEditGlobBashWebFetch
Path: library/specializations/domains/social-sciences-humanities/humanities/skills/topic-modeling-text-mining/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 1,642
Language: JavaScript

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Topic Modeling and Text Mining Apply LDA, NMF, and other computational methods to discover patterns in large text corpora with appropriate parameter tuning. ## Overview This skill enables computational analysis of large text collections. It encompasses topic modeling, text mining techniques, and pattern discovery to reveal structures and themes in textual data for humanistic inquiry. ## Capabilities ### Topic Modeling - LDA implementation - NMF analysis - Structural topic models - Dynamic topic models - Parameter optimization ### Text Preprocessing - Tokenization - Stopword removal - Lemmatization/stemming - N-gram extraction - Document-term matrices ### Pattern Discovery - Word frequency analysis - Collocation detection - Named entity recognition - Sentiment analysis - Network extraction ### Visualization - Word clouds - Topic distributions - Temporal trends - Network graphs - Interactive displays ## Usage Guidelines ### Analysis Process 1. Prepare text corpus 2. Preprocess documents 3. Select modeling approach 4. Tune parameters 5. Run analysis 6. Interpret results 7. Validate findings ### Parameter Considerations - Number of topics - Iteration counts - Hyperparameters - Cohere

What's inside
Steps it walks through
  1. Overview
  2. Capabilities
  3. Topic Modeling
  4. Text Preprocessing
  5. Pattern Discovery
  6. Visualization
  7. Usage Guidelines
  8. Analysis Process
  9. Parameter Considerations
  10. Interpretation Guidelines
  11. Integration Points
  12. Related Processes
  13. Collaborating Skills
  14. References
More from babysitter
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About this skill
What does the topic-modeling-text-mining skill do?

Apply LDA, NMF, and other computational methods to discover patterns in large text corpora with appropriate parameter tuning

How do I install it?

Run `npx skills add a5c-ai/babysitter --skill topic-modeling-text-mining --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From a5c-ai/babysitter, a repository with 1,642 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going