Automatically Detecting Amusing Games in Wordle
This is an incremental study for researchers interested in computational humor or game design, focusing on a specific domain (Wordle).
The paper tackled the problem of automatically predicting which Wordle games Reddit users find amusing by scraping 80k reactions and using GPT-3.5 for classification, finding that features from the games provide a weak signal for predicting amusement.
We explore automatically predicting which Wordle games Reddit users find amusing. We scrape approximately 80k reactions by Reddit users to Wordle games from Reddit, classify the reactions as expressing amusement or not using OpenAI's GPT-3.5 using few-shot prompting, and verify that GPT-3.5's labels roughly correspond to human labels. We then extract features from Wordle games that can predict user amusement. We demonstrate that the features indeed provide a (weak) signal that predicts user amusement as predicted by GPT-3.5. Our results indicate that user amusement at Wordle games can be predicted computationally to some extent. We explore which features of the game contribute to user amusement. We find that user amusement is predictable, indicating a measurable aspect of creativity infused into Wordle games through humor.