This one-day workshop provides a basic introduction to using artificial intelligence for text analysis. Tailored for researchers across a variety of social and health science fields, participants will gain practical skills in building text corpuses, topic modeling, and using ChatGPT, Copilot, and other Large Language Models (LLMs) in R, while addressing ethical considerations and validation techniques for AI-driven research.

Topics Covered
Pre-LLMs Techniques , Post-LLMs Insights , Choosing the Right Tools , Goals and Overview of Seminar , Precautions and Risks , Open and Closed LLMs , Introduction to Text-as-Data , Hands-On Exercise 1 , Data Collection Methods , Text Preprocessing , Managing Large Datasets , AI Assistance in R , Integrating Copilot , Integrating Chattr , Text-as-Data in R with Quanteda , Integrating Gptstudio , Hands-On Exercise 2 , API Key Set-Up , Basics of Topic Modeling , Understanding Embeddings , Analyzing Results , Useful R Packages and Applications , Hands-On Exercise 3 , Hands-On Exercise 4 , Using gpt-4o via API Key , Using llama3.2 locally , Working with Closed and Open LLMs , Using Gptstudio with an Open-Source LLM , Responsible AI Use , Validation Techniques , AI and Reproducibility , Transparency and Accessibility , Limitations of AI Assistance for Text Analysis , Hands-On Exercise 5 , Ethical Consideration and Sensitive Data , Effective Visualization , Wrap Up , Q+A , Useful Resources and Next Steps , Hands-On Exercise 6 , Examples from Political Communication Research