topic-modeling-text-mining

name	topic-modeling-text-mining
description	Apply LDA, NMF, and other computational methods to discover patterns in large text corpora with appropriate parameter tuning
allowed-tools	Read, Grep, Write, Edit, Glob, Bash, WebFetch
graph	{"domains":["domain:humanities"],"specializations":["specialization:digital-humanities"],"skillAreas":["skill-area:natural-language-processing","skill-area:machine-learning-frameworks","skill-area:data-analysis"],"workflows":["workflow:peer-review-cycle"],"roles":["role:data-scientist","role:computational-scientist"]}

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