4chan-pol-extensive / README.md
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metadata
language:
  - en
license: mit
task_categories:
  - text-classification
  - text-generation
task_ids:
  - multi-class-classification
  - language-modeling
size_categories:
  - 10K<n<100K
tags:
  - 4chan
  - internet-culture
  - text-data
pretty_name: 4chan /pol/ Dataset
pretty: true
dataset_info:
  features:
    - name: id
      dtype: int64
    - name: thread_id
      dtype: int64
    - name: board
      dtype: string
    - name: timestamp
      dtype: timestamp[ns]
    - name: title
      dtype: string
    - name: text
      dtype: string
    - name: text_length
      dtype: int64
    - name: filename
      dtype: string
    - name: file_ext
      dtype: string
    - name: file_size
      dtype: int64
    - name: image_width
      dtype: int64
    - name: image_height
      dtype: int64
    - name: is_op
      dtype: bool
    - name: mentions
      sequence: string
    - name: mention_count
      dtype: int64
    - name: replies
      dtype: int64
    - name: images
      dtype: int64
    - name: unique_ips
      dtype: int64
    - name: content_hash
      dtype: string
    - name: archived
      dtype: bool
    - name: semantic_url
      dtype: string
    - name: hour_of_day
      dtype: int32
    - name: day_of_week
      dtype: string
    - name: is_weekend
      dtype: bool
    - name: post_count
      dtype: int64
    - name: total_images
      dtype: int64
    - name: avg_text_length
      dtype: float64
    - name: std_text_length
      dtype: float64
    - name: total_mentions
      dtype: int64
  splits:
    - name: train
      num_bytes: 122600567
      num_examples: 317418
  download_size: 56680481
  dataset_size: 122600567
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*

4chan /pol/ dataset

This dataset contains data from 12000+ threads from 4chan boards, collected and processed for research purposes. The data includes both active and archived threads, with extensive metadata and derived features for studying online discourse and community dynamics.
I preserved thread structure, temporal information, and user interaction patterns while maintaining anonymity and excluding sensitive content.

Dataset Details

Dataset Description

  • Curated by: vmfunc
  • Language(s): English
  • License: MIT
  • Size: [Dataset size]
  • Number of Records:
    • Posts: 12435

Dataset Sources and Creation

The dataset was collected using a custom scraper that interacts with 4chan's official API.
Active threads are collected in real-time. Only publicly available data is collected and no PII is available. This data collection adheres to 4chan's robots.txt and API guidelines.
The collection process follows these steps:

Collection Process

  1. Active Threads: First, the scraper fetches the catalog of currently active threads from the board's catalog.json endpoint.

  2. Archive Integration: The scraper then queries the board's archive.json endpoint to obtain a list of archived thread IDs, ensuring comprehensive coverage of both current and historical content.

  3. Thread Processing: For each thread (both active and archived):

    • All posts within the thread are collected
    • HTML entities are decoded and tags are stripped while preserving line breaks
    • Mentions (>>post_numbers) are extracted and tracked
    • Post metadata (timestamps, file information, etc.) is preserved
    • Thread-level metrics are calculated (reply count, unique posters, etc.)
    • Temporal features are derived
    • Everything is processed in parallel (ThreadPoolExecutor)
    • MD5 hashing is used to identify and remove duplicate posts
    • All collected data is validated against a predefined schema

Uses

Direct Use

The dataset is suitable for:

  • Studying online discourse patterns and community dynamics
  • Analyzing temporal patterns in online discussions
  • Research on thread structure and user interaction patterns
  • Natural language processing tasks on informal internet communication
  • Content analysis and topic modeling
  • Network analysis of post references and replies

Out-of-Scope Use

This dataset should not be used for:

  • Identifying or tracking individual users
  • Generating harmful or malicious content
  • Training models for harassment or abuse
  • Analyzing sensitive personal information

Dataset Structure

Data Fields

Post-level Features

  • id: Unique post identifier (int64)
  • thread_id: Thread identifier (int64)
  • board: Board identifier (string)
  • timestamp: ISO format timestamp (timestamp[ns])
  • title: Thread or post title (string)
  • text: Clean post text content (string)
  • text_length: Length of the post text (int64)
  • filename: Original filename (string)
  • file_ext: File extension (string)
  • file_size: Size of attached file in bytes (int64)
  • image_width: Width of attached image (int64)
  • image_height: Height of attached image (int64)
  • is_op: Boolean indicating if post is the original post (bool)
  • mentions: List of post references (list)
  • mention_count: Number of mentions in the post (int64)
  • replies: Number of replies (int64)
  • images: Number of images (int64)
  • unique_ips: Number of unique IPs in thread (int64)
  • content_hash: MD5 hash of post content (string)
  • archived: Boolean indicating if thread is archived (bool)
  • semantic_url: Thread's semantic URL (string)

Thread-level Features

  • post_count: Total posts in thread (int64)
  • total_images: Total images in thread (int64)
  • avg_text_length: Average text length in thread (float64)
  • std_text_length: Standard deviation of text length (float64)
  • total_mentions: Total mentions in thread (int64)

Temporal Features

  • hour_of_day: Hour when post was made (int64)
  • day_of_week: Day of the week (string)
  • is_weekend: Boolean indicating weekend posts (bool)

Personal and Sensitive Information

  • All data is from public boards only
  • No IP addresses or unique identifiers included
  • Content hashing used for deduplication
  • No personal information preserved

Bias, Risks, and Limitations

Technical Limitations

  • Incomplete thread relationships due to archival
  • Missing posts due to deletion
  • Temporal gaps in archived content
  • File contents not included

Biases

  • Selection bias from board choice
  • Survivorship bias from archived content
  • Temporal bias from collection period
  • Community-specific language patterns

Risks

  • Potential for offensive content
  • Risk of harmful pattern learning
  • Bias in language models trained on the data

Dataset Card Authors

vmfunc

Dataset Card Contact

vmfunc