Elective: Text as Data

1. Text as Data 2. Text as Data as Measurement 3. Dictionaries (1. construction) 4. Dictionaries (2. evaluation and analysis) 5. Topic models (1. construction) 6. Topic models (2. extensions and limitations) 7. Space and Similarity 8. Sentiment 9. Scaling (1) 10. Scaling (2) 11. Text Classification 12. Causal Inference with Text

Scaling II

Extensions and Interpretation

Learning Objective: Understand extensions of association and correspondence analysis to multiple dimensions and their graphical interpretation

Lecture