Datasetpublic

trentmkelly/scored_co_2025

Scored.co 2025 scrape This dataset is a full scrape of public content from Scored.co, a right-wing Reddit-style social media site. It contains 73,045,361 rows of posts and comments, stored as parquet. The dataset is intended for research into online communities, political discussion, social media moderation, misinformation, platform migration, network dynamics, and large-scale text analysis. Data format The main dataset is partitioned by entity type:… See the full description on the dataset page: https://huggingface.co/datasets/trentmkelly/scored_co_2025.

sourceHugging Facecc-by-sa-4.0updated 5mo agoView on Hugging Face

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Dataset Card

Scored.co 2025 scrape

This dataset is a full scrape of public content from Scored.co, a right-wing Reddit-style social media site. It contains 73,045,361 rows of posts and comments, stored as parquet.

The dataset is intended for research into online communities, political discussion, social media moderation, misinformation, platform migration, network dynamics, and large-scale text analysis.

Data format

The main dataset is partitioned by entity type:

—entity_type=post/: post records
—entity_type=comment/: comment records

Hugging Face also provides converted parquet shards on the refs/convert/parquet branch, which can be useful for lightweight inspection or streaming workflows without downloading the full dataset.

Example:

python

from datasets import load_dataset

# Streams records without downloading the full dataset first.
ds = load_dataset(
    "trentmkelly/scored_co_2025",
    split="train",
    streaming=True,
)

for row in ds.take(3):
    print(row)

You can also work directly with parquet URLs or the hf:// filesystem interface if using tools such as DuckDB, Polars, PyArrow, or pandas.

Columns

A sample shard from refs/convert/parquet had the following fields:

Column	Description
`post_id`	Numeric Scored.co post ID.
`post_uuid`	Scored.co post UUID/string identifier.
`comment_id`	Numeric comment ID, when the row is a comment.
`comment_uuid`	Comment UUID/string identifier, when available.
`parent_id`	Parent post or comment identifier.
`author`	Public username associated with the record.
`community`	Scored.co community name.
`title`	Post title. For comments, this may repeat the parent post title.
`body`	Plain-text body/content extracted from the record.
`created_ms`	Creation timestamp in Unix milliseconds.
`created_iso`	Creation timestamp as an ISO-8601 UTC string.
`score`	Total score.
`score_up`	Upvote score/count, when available.
`score_down`	Downvote score/count, when available.
`comments_total`	Total comment count for post rows, when available.
`top_level_comments`	Top-level comment count for post rows, when available.
`depth`	Comment nesting depth, when available.
`is_deleted`	Whether the item was marked deleted.
`is_removed`	Whether the item was marked removed.
`is_nsfw`	Whether the item was marked NSFW.
`is_image`	Whether the item is an image post.
`is_video`	Whether the item is a video post.
`vote_state`	Vote-state value from the source record.
`pro_tier`	Source account/profile tier value.
`link`	Linked URL for link posts, when present.
`domain`	Domain extracted from `link`, when present.
`source_file`	Original scrape/source JSON filename.
`raw_json`	Raw source JSON payload retained as a string.

Some fields are entity-specific and may be null for posts or comments.

Notes and limitations

—This is scraped public web data and may include offensive, hateful, explicit, false, or otherwise sensitive content.
—Usernames and other public identifiers are included. Handle the data carefully and avoid attempts to identify, contact, harass, or profile individual users.
—Text may contain HTML-derived artifacts, links, markdown, quoted material, deleted/removed content markers, or source-platform metadata.
—The dataset reflects what was available to the scraper at collection time; it should not be treated as a complete or current representation of Scored.co.

Citation

If you use this dataset, cite the Hugging Face dataset repository:

bibtex

@dataset{kelly_scored_co_2025,
  author = {Kelly, Trent M.},
  title = {Scored.co 2025 scrape},
  year = {2025},
  publisher = {Hugging Face},
  url = {https://huggingface.co/datasets/trentmkelly/scored_co_2025}
}