Automatically Detecting Amusing Games in Wordle
Fuente:
arXiv
Saved in:
| Main Authors: | , , , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866908395399806976 |
|---|---|
| author | Luo, Ronaldo Liang, Gary Liu, Cindy Kabbara, Adam Bakhtawar, Minahil Kim, Kina Guerzhoy, Michael |
| author_facet | Luo, Ronaldo Liang, Gary Liu, Cindy Kabbara, Adam Bakhtawar, Minahil Kim, Kina Guerzhoy, Michael |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_05415 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Automatically Detecting Amusing Games in Wordle Luo, Ronaldo Liang, Gary Liu, Cindy Kabbara, Adam Bakhtawar, Minahil Kim, Kina Guerzhoy, Michael Computation and Language 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. |
| title | Automatically Detecting Amusing Games in Wordle |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2506.05415 |