topic-modeler
CommunityUncover insights with topic modeling.
Data & Analytics#document analysis#text analysis#topic modeling#natural language processing#keyword extraction#lda
Authordkyazzentwatwa
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill addresses the challenge of understanding large volumes of text by automatically identifying and summarizing the main themes present within a collection of documents.
Core Features & Use Cases
- LDA Topic Modeling: Utilizes Latent Dirichlet Allocation to discover underlying topics.
- Keyword Extraction: Identifies the most representative keywords for each topic.
- Document Classification: Assigns documents to their most probable topics.
- Visualization: Generates visual representations of topic distributions and word clouds.
- Use Case: A researcher analyzing thousands of customer reviews can use this Skill to quickly identify the top 5 recurring themes (e.g., "customer service," "product quality," "pricing") and understand the sentiment associated with each.
Quick Start
Run the topic modeler script on the 'reviews.csv' file, using the 'text' column to extract 5 topics and save the results to 'topics.json'.
Dependency Matrix
Required Modules
gensimnltkpandasmatplotlibwordcloudnumpy
Components
scripts
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: topic-modeler Download link: https://github.com/dkyazzentwatwa/chatgpt-skills/archive/main.zip#topic-modeler Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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