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7.57 kB
| dataset_info: | |
| features: | |
| - name: archived | |
| dtype: string | |
| - name: author | |
| dtype: string | |
| - name: author_fullname | |
| dtype: string | |
| - name: body | |
| dtype: string | |
| - name: comment_type | |
| dtype: string | |
| - name: controversiality | |
| dtype: string | |
| - name: created_utc | |
| dtype: string | |
| - name: edited | |
| dtype: string | |
| - name: gilded | |
| dtype: string | |
| - name: id | |
| dtype: string | |
| - name: link_id | |
| dtype: string | |
| - name: locked | |
| dtype: string | |
| - name: name | |
| dtype: string | |
| - name: parent_id | |
| dtype: string | |
| - name: permalink | |
| dtype: string | |
| - name: retrieved_on | |
| dtype: string | |
| - name: score | |
| dtype: string | |
| - name: subreddit_id | |
| dtype: string | |
| - name: subreddit_name_prefixed | |
| dtype: string | |
| - name: subreddit_type | |
| dtype: string | |
| - name: total_awards_received | |
| dtype: string | |
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| download_size: 109177016105 | |
| dataset_size: 255339788158 | |
| annotations_creators: | |
| - no-annotation | |
| language: | |
| - en | |
| language_creators: | |
| - found | |
| license: [] | |
| multilinguality: | |
| - monolingual | |
| pretty_name: Reddit comments | |
| size_categories: | |
| - 10B<n<100B | |
| source_datasets: [] | |
| tags: | |
| - social-media | |
| task_categories: | |
| - text-generation | |
| task_ids: | |
| - dialogue-modeling | |
| - language-modeling | |
| # Dataset Card for "REDDIT_comments" | |
| ## Dataset Description | |
| - **Homepage:** | |
| - **Paper: https://arxiv.org/abs/2001.08435** | |
| ### Dataset Summary | |
| Comments of 50 high-quality subreddits, extracted from the REDDIT PushShift data dumps (from 2006 to Jan 2023). | |
| ### Supported Tasks | |
| These comments can be used for text generation and language modeling, as well as dialogue modeling. | |
| ## Dataset Structure | |
| ### Data Splits | |
| Each split corresponds to a specific subreddit in the following list: "tifu", "explainlikeimfive", "WritingPrompts", "changemyview", "LifeProTips", "todayilearned", "science", "askscience", "ifyoulikeblank", "Foodforthought", "IWantToLearn", "bestof", "IAmA", "socialskills", "relationship_advice", "philosophy", "YouShouldKnow", "history", "books", "Showerthoughts", "personalfinance", "buildapc", "EatCheapAndHealthy", "boardgames", "malefashionadvice", "femalefashionadvice", "scifi", "Fantasy", "Games", "bodyweightfitness", "SkincareAddiction", "podcasts", "suggestmeabook", "AskHistorians", "gaming", "DIY", "mildlyinteresting", "sports", "space", "gadgets", "Documentaries", "GetMotivated", "UpliftingNews", "technology", "Fitness", "travel", "lifehacks", "Damnthatsinteresting", "gardening", "programming" | |
| ## Dataset Creation | |
| ### Curation Rationale | |
| All the information fields have been cast to string, as their format change through time from one dump to the following. A reduced number of keys have been kept: "archived", "author", "author_fullname", "body", "comment_type", "controversiality", "created_utc", "edited", "gilded", "id", "link_id", "locked", "name", "parent_id", "permalink", "retrieved_on", "score", "subreddit", "subreddit_id", "subreddit_name_prefixed", "subreddit_type", "total_awards_received". | |
| ### Source Data | |
| The [Reddit PushShift data dumps](https://files.pushshift.io/reddit/) are part of a data collection effort which crawls Reddit at regular intervals, to extract and keep all its data. | |
| #### Initial Data Collection and Normalization | |
| See the paper. | |
| #### Who are the source language producers? | |
| Redditors are mostly young (65% below 30), male (70%), and American (50% of the site). | |
| ### Personal and Sensitive Information | |
| The data contains Redditor's usernames associated to their content. | |
| ## Considerations for Using the Data | |
| This dataset should be anonymized before any processing. | |
| Though the subreddits selected are considered as being of higher quality, they can still reflect what you can find on the internet in terms of expressions of biases and toxicity. | |
| ### Contributions | |
| Thanks to [@clefourrier](https://github.com/clefourrier) for adding this dataset. |