PunkRockGirl/mass-contacts

Mass Contacts Database

A comprehensive public database of 186,699 contacts across entertainment, sports, music, and politics with verified social media handles.

Quick Start

from huggingface_hub import hf_hub_download
import sqlite3

# Download database
db_path = hf_hub_download(
    repo_id="PunkRockGirl/mass-contacts",
    filename="mass_contacts.db",
    repo_type="dataset"
)

# Query contacts with Twitter handles
conn = sqlite3.connect(db_path)
cursor = conn.execute("""
    SELECT full_name, twitter_handle, category
    FROM contacts
    WHERE twitter_handle IS NOT NULL
    LIMIT 10
""")

for name, handle, category in cursor:
    print(f"{name} (@{handle}) - {category}")

Dataset Summary

This dataset contains 186,699 public figures and influencers with their social media handles collected from public sources including IMDb, Wikipedia, ESPN, Billboard, and MusicBrainz.

Key Statistics:

• Total Contacts: 186,699
• With Social Media: 16,149 (8.6%)
• Twitter: 15,642 handles
• Instagram: 15,618 handles
• Facebook: 14,935 profiles
• TikTok: 14,187 handles
• YouTube: 558 channels
• Telegram: 1,634 usernames

Categories:

• Entertainment: 177,722 (95.2%)
• Music: 5,576 (3.0%)
• Sports: 3,382 (1.8%)
• Influencers: 17 (0.0%)
• Politics: 2 (0.0%)

Dataset Structure

Database Schema

SQLite database with 27 fields per contact:

Identity:

• id (INTEGER PRIMARY KEY)
• full_name (TEXT)
• first_name (TEXT)
• last_name (TEXT)
• middle_name (TEXT)

Classification:

• category (TEXT) - ENTERTAINMENT, MUSIC, SPORTS, POLITICS, INFLUENCER
• subcategory (TEXT) - actor, director, musician, athlete, etc.
• occupation (TEXT)
• designation (TEXT)

Social Media:

• twitter_handle (TEXT)
• instagram_handle (TEXT)
• facebook_handle (TEXT)
• tiktok_handle (TEXT)
• youtube_channel (TEXT)
• telegram_username (TEXT)
• linkedin_handle (TEXT)
• bluesky_handle (TEXT)

Contact Info:

• email (TEXT)
• phone (TEXT)
• website (TEXT)

Biographical:

• birth_date (DATE)
• birth_place (TEXT)
• sun_sign (TEXT)
• nationality (TEXT)

References:

• imdb_id (TEXT) - IMDb nconst identifier
• source_url (TEXT)
• data_source (TEXT) - imdb_dataset, espn, billboard, etc.

Metadata:

• stage_completed (INTEGER) - Processing stage (1-3)
• created_at (TIMESTAMP)

Data Sources

All data extracted from publicly available sources:

1. IMDb Official Dataset (181,983 contacts)

   • Source: https://datasets.imdbws.com/
   • File: name.basics.tsv.gz
   • License: Non-commercial use only
   • Data: Names, birth years, professions

2. IMDb Person Pages (16,149+ enriched)

   • Source: Individual IMDb person pages
   • Data: Twitter, Instagram, Facebook, TikTok, YouTube handles
   • Method: Publicly listed social media links

3. ESPN Sports Data (3,382 contacts)

   • Source: ESPN player pages
   • Data: Athletes across major sports
   • Categories: NFL, NBA, MLB, NHL, MLS, Soccer

4. Billboard Charts (2,100+ contacts)

   • Source: Billboard Hot 100 archives
   • Data: Musicians, artists, producers
   • Categories: Pop, Rock, Hip-Hop, Country, etc.

5. MusicBrainz (3,476+ contacts)

   • Source: MusicBrainz open music encyclopedia
   • Data: Artists, composers, producers
   • License: CC0 Public Domain

6. Wikipedia/Wikidata (Social enrichment)

   • Source: Wikipedia infoboxes, Wikidata properties
   • Data: Social media handles (P2002, P2003, P8265, etc.)
   • License: CC0 Public Domain

Usage Examples

Basic Queries

import sqlite3

conn = sqlite3.connect('mass_contacts.db')

# Get all contacts with Twitter handles
twitter_users = conn.execute("""
    SELECT full_name, twitter_handle, category
    FROM contacts
    WHERE twitter_handle IS NOT NULL
""").fetchall()

# Get musicians with Instagram
musicians = conn.execute("""
    SELECT full_name, instagram_handle
    FROM contacts
    WHERE category = 'MUSIC'
    AND instagram_handle IS NOT NULL
""").fetchall()

# Get athletes with multiple platforms
athletes = conn.execute("""
    SELECT full_name, twitter_handle, instagram_handle, tiktok_handle
    FROM contacts
    WHERE category = 'SPORTS'
    AND twitter_handle IS NOT NULL
    AND instagram_handle IS NOT NULL
""").fetchall()

Export to CSV

import pandas as pd
import sqlite3

conn = sqlite3.connect('mass_contacts.db')

# Export all contacts with social media
df = pd.read_sql("""
    SELECT full_name, category, subcategory,
           twitter_handle, instagram_handle, facebook_handle,
           tiktok_handle, youtube_channel, imdb_id
    FROM contacts
    WHERE twitter_handle IS NOT NULL
       OR instagram_handle IS NOT NULL
       OR facebook_handle IS NOT NULL
       OR tiktok_handle IS NOT NULL
""", conn)

df.to_csv('contacts_with_social.csv', index=False)
print(f"Exported {len(df)} contacts")

Create Distribution Lists

import sqlite3

conn = sqlite3.connect('mass_contacts.db')

# Twitter distribution list
twitter_list = conn.execute("""
    SELECT twitter_handle FROM contacts
    WHERE twitter_handle IS NOT NULL
""").fetchall()

with open('twitter_handles.txt', 'w') as f:
    for (handle,) in twitter_list:
        f.write(f"@{handle}\n")

print(f"Created Twitter list with {len(twitter_list)} handles")

# Instagram distribution list
instagram_list = conn.execute("""
    SELECT instagram_handle FROM contacts
    WHERE instagram_handle IS NOT NULL
""").fetchall()

with open('instagram_handles.txt', 'w') as f:
    for (handle,) in instagram_list:
        f.write(f"@{handle}\n")

print(f"Created Instagram list with {len(instagram_list)} handles")

Filter by Category

import sqlite3

conn = sqlite3.connect('mass_contacts.db')

# Get all actors with Twitter
actors = conn.execute("""
    SELECT full_name, twitter_handle
    FROM contacts
    WHERE subcategory LIKE '%actor%'
    AND twitter_handle IS NOT NULL
""").fetchall()

# Get all musicians with Instagram
musicians = conn.execute("""
    SELECT full_name, instagram_handle
    FROM contacts
    WHERE category = 'MUSIC'
    AND instagram_handle IS NOT NULL
""").fetchall()

# Get all athletes with TikTok
athletes = conn.execute("""
    SELECT full_name, tiktok_handle
    FROM contacts
    WHERE category = 'SPORTS'
    AND tiktok_handle IS NOT NULL
""").fetchall()

Data Fields

Field	Type	Description	Example
id	INTEGER	Unique identifier	1
full_name	TEXT	Full name	"Tom Hanks"
first_name	TEXT	First name	"Tom"
last_name	TEXT	Last name	"Hanks"
category	TEXT	Main category	"ENTERTAINMENT"
subcategory	TEXT	Specific role	"actor"
twitter_handle	TEXT	Twitter username	"tomhanks"
instagram_handle	TEXT	Instagram username	"tomhanks"
facebook_handle	TEXT	Facebook username	"TomHanks"
tiktok_handle	TEXT	TikTok username	"tomhanks"
youtube_channel	TEXT	YouTube channel ID	"UC..."
telegram_username	TEXT	Telegram username	"tomhanks"
linkedin_handle	TEXT	LinkedIn username	"tomhanks"
bluesky_handle	TEXT	Bluesky handle	"tomhanks.bsky.social"
email	TEXT	Public email	"contact@example.com"
phone	TEXT	Public phone	"+1-555-0100"
website	TEXT	Official website	"https://example.com"
birth_date	DATE	Birth date	"1956-07-09"
birth_place	TEXT	Birth location	"Concord, California"
sun_sign	TEXT	Astrological sign	"Cancer"
nationality	TEXT	Nationality	"American"
imdb_id	TEXT	IMDb identifier	"nm0000158"
source_url	TEXT	Original source	"https://www.imdb.com/name/nm0000158/"
data_source	TEXT	Source system	"imdb_dataset"
stage_completed	INTEGER	Processing stage	3
created_at	TIMESTAMP	Import timestamp	"2026-02-15 10:30:00"

Statistics

Overall:

• Total Contacts: 186,699
• With Social Media: 16,149 (8.6%)
• With IMDb IDs: 181,627 (97.3%)

By Platform:

• Twitter: 15,642 (8.4%)
• Instagram: 15,618 (8.4%)
• Facebook: 14,935 (8.0%)
• TikTok: 14,187 (7.6%)
• YouTube: 558 (0.3%)
• Telegram: 1,634 (0.9%)
• LinkedIn: 0 (0.0%)
• Bluesky: 0 (0.0%)

By Category:

• Entertainment: 177,722 (95.2%)
• Music: 5,576 (3.0%)
• Sports: 3,382 (1.8%)
• Influencers: 17 (0.0%)
• Politics: 2 (0.0%)

Entertainment Breakdown:

• Actors: 144,526
• Directors: 18,992
• Producers: 14,204

Music Breakdown:

• Artists: 3,476
• Musicians: 2,100

Sports Breakdown:

• Football: 1,245
• Basketball: 892
• Baseball: 654
• Hockey: 356
• Soccer: 235

Limitations

1. Social Media Coverage: Only 8.6% of contacts have social media handles

   • Many public figures don't list social media on IMDb
   • Some platforms (LinkedIn, Bluesky) not yet scraped
   • Collection ongoing - percentage will increase

2. IMDb Dataset Bias: 95% of contacts are from entertainment industry

   • IMDb dataset is entertainment-focused
   • Sports, music, politics underrepresented
   • Expanding to other sources in progress

3. Handle Verification: Social media handles extracted from public listings

   • Handles scraped from IMDb person pages
   • Some may be outdated or inactive
   • No verification of account ownership

4. Deceased Individuals: Dataset includes deceased persons

   • IMDb dataset includes historical figures
   • No filtering by death date applied
   • Use death_date field if needed (not yet populated)

5. Privacy: Only publicly listed information included

   • All handles from publicly accessible pages
   • No private/unlisted accounts
   • No email/phone unless publicly listed

6. Completeness: Data collection ongoing

   • 181K+ IMDb contacts still being processed
   • Current enrichment rate: ~1,140 contacts/hour
   • Estimated completion: Several days

Ethical Considerations

Public Data Only:

• All information scraped from publicly accessible sources
• Social media handles publicly listed on IMDb, Wikipedia
• No private data, no scraping of protected content
• Respects robots.txt and rate limits

Intended Use:

• Research and analysis
• Outreach and communication
• Marketing and PR campaigns
• NOT for harassment or spam

Responsible Usage:

• Use for legitimate communication only
• Respect social media platform terms of service
• Do not use for unsolicited bulk messaging
• Follow anti-spam laws (CAN-SPAM, GDPR, etc.)

Privacy Protection:

• No private contact information included
• No unlisted social media accounts
• No personal data beyond public profiles
• Users can request removal (see Contact)

Updates

Collection Status:

• Ongoing scraping from IMDb person pages
• Rate: ~1,140 contacts enriched per hour
• Current: 16,149 with social media (8.6%)
• Target: 181,627 IMDb contacts (97%+ coverage)

Planned Expansions:

• LinkedIn handle scraping
• Bluesky handle scraping
• Email extraction from official websites
• Death date population from IMDb
• Additional sports sources (ESPN, team rosters)
• Additional music sources (Spotify, Apple Music)
• Political figures (FEC, Congress.gov)

Re-upload Schedule:

• Database re-uploaded weekly as scraping continues
• Check dataset page for latest upload timestamp
• Statistics updated with each upload

Last Updated: 2026-02-15 Next Update: 2026-02-22 (estimated)

Citation

If using this dataset in research or projects, please cite:

@dataset{mass_contacts_2026,
  author = {Casey, Tammy L.},
  title = {Mass Contacts Database},
  year = {2026},
  publisher = {HuggingFace},
  url = {https://huggingface.co/datasets/PunkRockGirl/mass-contacts},
  note = {186,699 public figures with social media handles}
}

License

CC0 1.0 Universal (Public Domain)

This dataset is released to the public domain under CC0 1.0.

You can:

• Copy, modify, distribute the data
• Use for commercial purposes
• Use without attribution (though appreciated)

No copyright. No restrictions. Free for any use.

Source Attribution:

• IMDb data: For non-commercial use only (IMDb terms)
• Other sources: Public domain or CC0

Contact

Corrections & Updates:

• Found an error? Submit an issue on GitHub
• Missing social handle? Submit correction
• Want to be removed? Contact via dataset page

Technical Support:

• Questions about dataset structure
• Help with queries or integration
• Bug reports for database issues

Repository: https://github.com/PunkRockGirl/mass-contacts

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Disclaimer: This dataset contains publicly available information only. Presence in this database does not imply endorsement or consent for contact. Use responsibly and ethically. Follow all applicable laws and platform terms of service.