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--- |
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license: cc-by-4.0 |
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task_categories: |
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- text-generation |
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language: |
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- en |
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size_categories: |
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- 1K<n<10K |
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--- |
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# Dataset Summary |
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The "humor-chains" dataset is a machine-filtered collection of the most upvoted Reddit submissions and their replies on humor-related subreddits. Generally, a humor chain is when a short post triggers a chain of one or more replies *that Redditors find entertaining*. In other words, some entries might be NSFW, topical, or internal jokes. |
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For example ([original thread](https://www.reddit.com/r/funny/comments/cmb3z/im_dating_a_midget/?sort=top)): |
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# Dataset Details |
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## License |
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[CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/deed.en) |
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Note that the dataset was created from Reddit's public user-generated content. |
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Reddit's license states in section "2.4 User Content" that such content is [ownership of individual reddit users](https://www.redditinc.com/policies/data-api-terms#:~:text=2.4%20User%20Content,not%20by%20Reddit.) and not Reddit itself. |
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For privacy reasons, all usernames were removed and replaced by "human" (original submission) and "gpt" (all replies). |
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That format is convenient for fine-tuning GPT models, e.g., in [Axolotl](https://github.com/OpenAccess-AI-Collective/axolotl) that is ["sharegpt" format type](https://openaccess-ai-collective.github.io/axolotl/docs/dataset-formats/conversation.html#sharegpt). |
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UPDATE 2024-7-9: Axolotl's finetuning formats expect a single GPT reply, so dataset was reduced to include submission and a single top reply. |
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## Dataset Creation |
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The dataset was created using the following procedure: |
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1. Reddit's API was not used directly, as API license switched to a more restrictive license (see [2023 Reddit API controversy](https://en.wikipedia.org/wiki/2023_Reddit_API_controversy)). Instead, I used older Reddit dump [Subreddit comments/submissions 2005-06 to 2023-12](https://academictorrents.com/details/56aa49f9653ba545f48df2e33679f014d2829c10). Inside the big torrent file are zstandard compressed ndjson files, each representing a subreddit. |
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2. Downloaded a portion of subreddits from [List of funny subreddits](https://www.reddit.com/r/redditlists/comments/128ayc/list_of_funny_subreddits/). |
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3. Python script filtered .jsonl files inside .zst to include only the most upvoted thread for each submission. |
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4. Filtered submissions satisfy ALL of the following: |
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* score >= min (10 upvotes), |
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* total len is shorter than max_text_len (256 characters), |
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* title is not "[deleted by user]", |
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* selftext is not "[removed]" or "[deleted]", |
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* links to itself (Reddit link) and not an image, video, or external link, |
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* doesn't start with a link, |
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* doesn't have a thumbnail. |
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5. Filtered comments satisfy ALL of the following: |
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* score >= min (5 upvotes), |
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* total len is shorter than max_text_len (256 characters), |
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* Only top upvoted reply at each reply level is included. |
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6. All filtered threads were further filtered with a local model for humor detection: [Humor-Research/humor-detection-comb-23](https://huggingface.co/Humor-Research/humor-detection-comb-23/tree/main), which was selected because it performed the best on [lm233/humor_train](https://huggingface.co/datasets/lm233/humor_train?row=9) dataset. Threads not detected as funny were removed. |
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All code used for filtering of the dataset is available on GitHub: [reddit-filter](https://github.com/ZSvedic/reddit-filter) |
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## Citation |
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``` |
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@misc{ZSvedic_humor_chains, |
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title={humor-chains}, |
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author={Zeljko Svedic}, |
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year={2024}, |
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url={https://huggingface.co/datasets/ZSvedic/humor-chains/blob/main/README.md} |
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} |
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``` |
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## Curated by |
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[Zeljko Svedic](https://huggingface.co/ZSvedic) |
