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text-analyst

Analyze sociological text data with topic modeling, sentiment, or classification in R or Python.

76|9|Updated Jan 17, 2026
Search Tags:#embeddings#classification#reproducibility#text-analysis#topic-modeling#sentiment-analysis#sociology
One-click install
npx skills add https://github.com/nealcaren/social-data-analysis --skill text-analyst
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: text-analyst
Source: https://github.com/nealcaren/social-data-analysis/tree/main/plugins/text-analyst/skills/text-analyst
Command: npx skills add https://github.com/nealcaren/social-data-analysis --skill text-analyst

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill provides a structured, reproducible workflow for analyzing sociological text data using R or Python, guiding users from data preparation to publication-ready results.

Core Features & Use Cases

  • Phase-based workflow with mandatory pauses for user review and decision-making.
  • Supports Topic Modeling (LDA/STM/BERTopic), sentiment analysis, supervised classification, and embeddings.
  • Enables generation of publication-ready outputs with provenance, documentation, and diagnostics.

Quick Start

Define your research question and corpus, choose language (R or Python), and initiate Phase 0 to design, Phase 1 to prepare, Phase 2 to specify, Phase 3 to analyze, Phase 4 to validate, and Phase 5 to interpret results.

Frequently Asked Questions about text-analyst

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I perform reproducible text analysis for sociological research?▼

Reproducible text analysis for sociology uses a phase-driven workflow guiding users from data preparation through validation, ensuring publication-ready results with complete provenance and an auditable preprocessing trail.

What is the best way to apply topic modeling and sentiment analysis to a text corpus?▼

Applying topic modeling and sentiment analysis requires a phase-driven workflow that supports LDA, STM, BERTopic, and supervised classification, ensuring validation and interpretability for sociological research questions.

Can I use R or Python for sociological text classification and embeddings?▼

Yes, R or Python can be used for sociological text classification and embeddings, applying topic modeling, sentiment, or classification as appropriate to the research question while ensuring validation and interpretability.

How do I validate and interpret sociological text analysis results for publication?▼

Validating and interpreting sociological text analysis results involves a phase-driven workflow with mandatory pauses for review, ensuring publication-ready outputs with documentation, diagnostics, and an auditable preprocessing trail.

Does this text analysis workflow support supervised classification and BERTopic?▼

Yes, the text analysis workflow supports supervised classification and BERTopic, alongside LDA, STM, sentiment analysis, and embeddings, applying each technique as appropriate to the research question.

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