Module 3: The Text Branch
When Words Become Data
Learning Objectives
- Process text as research data with NLP
- Detect emotion in text using VADER sentiment analysis
- Understand word embeddings as meaning geometry
- Discover hidden themes with LDA topic modeling
- Extract signals from innovator language patterns
Topics
| Topic | Type |
|---|---|
| Decision Tree Navigator | Opening |
| People Reveal Things They Didn’t Intend To | Hook |
| Text as Research Data | Lecture |
| The NLP Pipeline | Lecture |
| Sentiment Analysis | Lecture |
| Word Embeddings: Meaning as Geometry | Lecture |
| NLP Demo | Live Demo |
| Topic Modeling: Hidden Themes | Lecture |
| LDA: Latent Dirichlet Allocation | Lecture |
| Topic Modeling Demo | Live Demo |
| Your Turn: Where Does This Fit? | Socratic |
| Map Check: Where Are We? | Discussion |