Week 06: Text to data with AI

## Overview Continue using text for research with AI ### Learning Outcomes By the end of the session, students will: * Gain hands-on experience with sentiment analysis. * Have experience integrating NLP in research * Think about what is ground truth ### Materials **Datasets** - texts (text_id level) - games info (such as results, text_id level) - class-ratings (human, AI ratio, text_id*student level) - domain-rating (text_id level) - class-rating-aggregated (text_id level) **code** code that creates the combined data ## Preparation * Download the combined data from Moodle * Note: win, draw -- need encode loss ## Class tasks ### Discussion 1 * Your experience regarding human vs ai ratings. * What was difficult and easy as human rater ### Data Analysis * Take the aggregated file and ask AI for a readme. Discuss what is in the data * Compare human, domain lexicon and AI rating. For human and AI take the average. * Think of an interesting comparison using AI rating * Compare results by human and lexicon rating ### Discussion 2 * What is ground truth ### How to integrate AI into research * combine data with text * think RQ and how you'd use AI ## Additional tasks if time permits ### predict gender and result * Show AI all texts and ask to predict the gender of speaker * Show AI all texts and ask to predict the result (manager's team won, drew, lost)