Social Analyzer - Find Social Profiles by Username

Type a username and get every public profile that uses it. Every run checks all 999 sites the scanner knows: social networks, gaming, dating, developer, forums, wikis and niche platforms. Every hit is ranked high, medium or low confidence with the page's title, language and meta tags, so real profiles come first and guesses stay marked. No login, no cookies, no API key.

Available as an Apify Actor. $0.005 per profile found. One username on all 999 sites takes about 3 minutes; on the 100 most popular sites about 30 seconds.

What does it do?

You give it one username, or a list, and nothing else is needed: with only the username set, the scan is the widest possible, all 999 sites, worldwide, every category, every match kept and labelled by confidence, page details and patterns extracted, one hour to do it. It checks those sites for a profile with exactly that handle and returns one row per profile it finds: the platform, the profile URL, how confident the match is, the site's category and country, the page title, its language and its meta tags. A summary row and an OUTPUT record say in plain words what was checked, how many sites had no profile, how many did not answer, and what came back.

You can paste @elonmusk or a full profile link like twitter.com/elonmusk; the handle is taken out of it. If you paste an email address, the part before the @ is searched and the run points you to the email tool for the address itself.

How is it different from Sherlock?

The scanner underneath is qeeqbox/social-analyzer (3,000+ GitHub stars). This actor runs it at full depth on every run: all sites, all output fields, 60 parallel workers instead of its hardcoded 15, and its most permissive detection level. It also chooses the sites itself from the scanner's own list and fixes what the command line gets wrong in the current version: several usernames at once, category and country filters, a confidence filter that silently did nothing, and the slow and special modes that have no code behind them.

When should I use it?

• Recruiting and hiring: check a candidate's public presence from one handle
• People search: find every account a person uses under a username
• Fraud and trust teams: find a scammer's or seller's other profiles
• Dating safety and self-checks: see what a handle exposes, including on dating and adult sites
• Investigations and due diligence: build a cross-platform footprint for a case

What does it cost?

Typical runs:

A run that finds nothing costs nothing. Runs stopped by your own input (no username, filters that match no site) cost nothing. If a run is cut off by the time limit or your spending limit, you keep and pay for only the rows delivered before the cut.

Which inputs does it take?

Filters combine. With a category or country filter, top picks the most popular sites inside that filter. With websites, top is ignored.

Nothing is held back. The scanner offers three modes; only fast has code behind it in the current version, and its internal "extreme" level is a stricter gate that returns fewer hits, not a deeper scan. So every run already uses the deepest configuration that exists: all sites, all fields, the permissive level. The only feature not exposed is profile screenshots, which needs a Chrome browser the image does not carry.

How do I follow a run?

The status line at the top of the run updates after every step: 48% done: 500 of 998 site checks, 143 profiles so far. 1 of 3 usernames finished, now checking kaytats. Rows appear in the dataset as each step (about 250 sites) finishes, so you can start reading results after about 30 seconds. The OUTPUT record carries status, percentDone and per-username progress while the run is going, and turns into the final summary when it ends.

What does the output look like?

Real rows from a local run on 2026-09-12 with input {"username": "frostkatrina@ymail.com", "top": 50}. The address was recognised as an email, the handle frostkatrina was searched, 17 profiles came back in 37 seconds.

One profile row as JSON:

{
  "recordType": "profile",
  "username": "torvalds",
  "platform": "GitHub",
  "site": "github.com",
  "link": "https://github.com/torvalds",
  "confidence": "high",
  "matchRate": 100.0,
  "category": "developer_tech",
  "categoryDetail": "Computers Electronics and Technology > Programming and Developer Software",
  "country": "United States",
  "adultSite": false,
  "siteRank": 89,
  "pageTitle": "torvalds (Linus Torvalds)",
  "language": "English",
  "metadata": [{"property": "og:title", "content": "torvalds - Overview"}, {"property": "og:type", "content": "profile"}],
  "checkedAt": "2026-09-12T14:20:11+00:00"
}

The summary row (also saved as the OUTPUT record) from the same email run:

{
  "recordType": "summary",
  "usernames": ["frostkatrina"],
  "usernamesChecked": 1,
  "sitesPerUsername": 50,
  "filters": {},
  "profilesFound": 17,
  "highConfidence": 2,
  "mediumConfidence": 11,
  "lowConfidence": 4,
  "sitesNotFound": 29,
  "sitesFailed": 4,
  "durationSeconds": 36.5,
  "notes": ["\"frostkatrina@ymail.com\" is an email address. Searched the part before the @ (\"frostkatrina\") as a username. To find accounts registered with the email itself, use https://apify.com/anshumanatrey/holehe-email-osint"],
  "message": "Found 17 profiles for frostkatrina across 50 sites: 2 high, 11 medium, 4 low confidence. Strongest first. ..."
}

Confidence. High means a 100% match: the site answered exactly the way it does for a real profile. Medium (50 to 99%) is likely but worth a look; many adult and dating sites answer at 50% for any handle. Low is a guess. Rows are sorted strongest first. The default keeps everything, so a bare username misses nothing; choose "Confident and possible" or "Confident matches only" for a cleaner list.

Common questions

Q: I typed several usernames and got one weird result. Separate them with commas or use the bulk list. Each username is checked on its own; a name with a space in it is rejected with a message, because usernames have no spaces.

Q: I pasted an email address. The run searches the part before the @ as a username and tells you so in the summary. To find which sites an email is registered on, use holehe-email-osint.

Q: The category or country filter returned nothing. The run stops with a message when your filters match no site, so you pay nothing. Loosen one filter. Category counts are shown in the dropdown; most sites in the list are American or Indian.

Q: My run found nothing. The status message says so plainly, and the summary tells you how many sites had no profile and how many did not answer. Check the spelling, or switch to "Confident and possible matches" to see weaker matches. A handle that exists nowhere returns one summary row.