metadata

annotations_creators:
  - found
language:
  - en
language_creators:
  - found
license:
  - unknown
multilinguality:
  - monolingual
pretty_name: >-
  English haiku dataset scraped from Reddit's /r/haiku with topics extracted
  using KeyBERT
size_categories:
  - 10K<n<100K
source_datasets:
  - extended|other
tags:
  - haiku
  - poem
  - poetry
  - reddit
  - keybert
  - generation
task_categories:
  - text-generation
task_ids:
  - language-modeling

Dataset Card for "Reddit Haiku"

This dataset contains haikus from the subreddit /r/haiku scraped and filtered between October 19th and 10th 2022, combined with a previous dump of that same subreddit packaged by ConvoKit as part of the Subreddit Corpus, which is itself a subset of pushshift.io's big dump.

A main motivation for this dataset was to collect an alternative haiku dataset for evaluation, in particular for evaluating Fabian Mueller's Deep Haiku model which was trained on the Haiku datasets of hjhalani30 and bfbarry, which are also available on huggingface hub.

Fields

The fields are post id (id), the content of the haiku (processed_title), upvotes (ups), and topic keywords (keywords). Topic keywords for each haiku have been extracted with the KeyBERT library and truncated to top-5 keywords.

Usage

This dataset is intended for evaluation, hence there is only one split which is test.

from datasets import load_dataset

d=load_dataset('huanggab/reddit_haiku', data_files='test':'merged_with_keywords.csv'})  # use data_files or it will result in error
>>> print(d['train'][0])
#{'Unnamed: 0': 0, 'id': '1020ac', 'processed_title': "There's nothing inside/There is nothing outside me/I search on in hope.", 'ups': 5, 'keywords': "[('inside', 0.5268), ('outside', 0.3751), ('search', 0.3367), ('hope', 0.272)]"}

There is code for scraping and processing in processing_code, and a subset of the data with more fields such as author Karma, downvotes and posting time at processing_code/reddit-2022-10-20-dump.csv.