SarcasmNet/self-annotated_reddit_climate_comment

{
  "id": "1006cei",
  "post_title": "Amazing Water Filter Invention",
  "post_author": "User123",
  "post_body": "Check out this incredible water filter!",
  "post_url": "https://example.com/water_filter",
  "post_pic": "https://example.com/images/water_filter.jpg",
  "subreddit": "inventions",
  "post_timestamp": "2023-01-01T12:00:00Z",
  "post_upvotes": 123,
  "post_permalink": "/r/inventions/comments/1006cei/amazing_water_filter_invention/",
  "comments": {
    "CommentID": ["abc123", "def456"],
    "CommentAuthor": ["User456", "User789"],
    "CommentBody": ["This is awesome!", "How does it work?"],
    "CommentTimestamp": ["2023-01-01T12:30:00Z", "2023-01-01T13:00:00Z"],
    "CommentUpvotes": [5, 7],
    "CommentPermalink": ["/r/inventions/comments/1006cei/amazing_water_filter_invention/abc123/", "/r/inventions/comments/1006cei/amazing_water_filter_invention/def456/"],
    "Label": [1,0]
    ]
  }
}

id: string - Unique identifier for the post.
post_title: string - Title of the post.
post_author: string - Username of the author who posted.
post_body: string - Body/content of the post.
post_url: string - URL of the post.
post_pic: Image - Image associated with the post.
subreddit: string - Subreddit where the post was made.
post_timestamp: string - Timestamp of when the post was made.
post_upvotes: int32 - Number of upvotes the post received.
post_permalink: string - Permanent link to the post.
comments: Sequence - Sequence of comments associated with the post.
- CommentID: string - Unique identifier for the comment.
- CommentAuthor: string - Username of the comment author.
- CommentBody: string - Content/body of the comment.
- CommentTimestamp: string - Timestamp of when the comment was made.
- CommentUpvotes: int32 - Number of upvotes the comment received.
- CommentPermalink: string - Permanent link to the comment.
- Label: int32 - Label a comment as sarcastic or neutral (1 or 0).

@InProceedings{huggingface:dataset,
title = {Self-annotated Reddit Climate Comment},
author={Catherine Wang, Ziyuan Ma},
year={2024}
}