How does it handle version control during analysis?

The skill uses a git-based workflow to track progress across five distinct analysis phases, ensuring reproducibility without creating messy version-suffixed files.

Can I use it for sentiment analysis?

Absolutely. It includes dedicated guides for both dictionary-based approaches in R and machine learning or transformer-based approaches in Python.

Is validation included in the process?

Yes, systematic validation is a core principle. The skill guides you through human coding, diagnostics, and sensitivity analysis to ensure publication-ready results.

Does this skill support both R and Python?

Yes, it provides specific guidance and technique guides for both languages, recommending R for traditional topic models (STM) and Python for neural methods like BERTopic.

What specific models are supported?

It supports a wide range of methods including LDA, Structural Topic Models (STM), BERTopic, Word Embeddings (Word2Vec, GloVe), and Supervised Classification.

Sociology Text Analyst

Name: Sociology Text Analyst
Author: nealcaren

bynealcaren

•

データサイエンスとML

Conducts systematic computational text analysis for sociology research using R or Python with a focus on validation and reproducibility.

The Sociology Text Analyst skill empowers researchers to perform rigorous computational text analysis within the Claude Code environment. It provides a structured, multi-phase framework covering everything from initial research design and method selection (such as STM or BERTopic) to systematic validation and the generation of publication-ready tables and figures. By integrating best practices from social science, it ensures that text analysis results are not just computationally sound but also theoretically valid and reproducible, supporting both R's statistical depth and Python's neural network capabilities.

主な機能

01Automated version control integration using git to track analysis decisions and iterations

02Comprehensive validation strategies including human coding, diagnostics, and sensitivity analysis

033 GitHub stars

04In-depth conceptual guides for advanced NLP methods specifically tailored for social science research

05Dual-language support for both R (STM, tidytext) and Python (spaCy, BERTopic, Transformers)

06Structured five-phase analysis workflow from research design to final interpretation

ユースケース

01Developing and validating custom sentiment lexicons or supervised classifiers for specific sociological domains

02Implementing neural topic models like BERTopic for exploratory analysis of social media data in Python

03Performing structural topic modeling (STM) on large sets of interview transcripts or news articles in R

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add nealcaren/sociology-skillset text-analyst

For use in Claude.ai and ChatGPT

Download Skill