1,000,000 Reddit posts and comments from the /r/jokes subreddit, each annotated with its community score. The collection includes unique base-36 identifiers and distinguishes between top-level submissions and replies via a type field.
Use Cases
- Predict the 'score' of a joke by training a model on the text content and associated metadata
- Classify entries as 'post' or 'comment' to study structural differences in humor delivery
- Fine-tune large language models for humor generation using the one million text samples
- Conduct longitudinal studies of subreddit trends using the unique 'id' and 'subreddit.id' fields
Strengths
- 1,000,000 labeled entries from the /r/jokes subreddit
- Includes a 'score' column representing the net upvotes for each joke
- Categorizes data points using the 'type' field as either 'post' or 'comment'
- Features unique base-36 'id' and 'subreddit.id' strings for precise data tracking