URL: /docs/guides/linked-from
---
title: Expired domains with Wikipedia, university and gov links
sidebarTitle: By linking site
description: Use the source filter to find expired domains that still carry links from Wikipedia, Hacker News, universities and government bodies — and read linked_by to judge them.
icon: link
---
A small number of links from sites with real editorial standards is often worth more than hundreds of anonymous ones. Revised names those sites on every listing, in `linked_by`, and lets you filter the directory on them with `source`. This guide finds expired domains still linked from Wikipedia, from universities and from government bodies, and shows how to read what comes back.
It assumes you have an API key and have run the [Quickstart](/docs/quickstart).
## How named linkers work
Every listing carries `linked_by`: the recognisable sites among its linkers, by display name.
```json
"linked_by": ["Cornell University", "United Nations"]
```
The names come from a catalogue of 297 sources as of 23 September 2026 — encyclopedias, developer platforms, communities, news outlets, 45 universities and 20 government and intergovernmental bodies. A site that is not in the catalogue can still link to a domain; it counts toward `referring_domains` but is not named.
## Filter on one source
`source` takes a display name exactly as it appears in `linked_by`. Case is preserved, so send `Wikipedia`, not `wikipedia`.
```bash
curl -s -G https://getrevised.com/api/v1/domains \
-H "Authorization: Bearer $REVISED_API_KEY" \
--data-urlencode "source=Wikipedia" \
-d tier=open \
-d spam=low \
-d limit=50
```
`--data-urlencode` matters as soon as a name has a space in it: `Hacker News`, `Cornell University`, `United Nations`.
## Filter on several
Comma-separate names to match **any** of them. This is how you ask for "linked from a university" or "linked from a government body": list the institutions you care about.
```python
import os
import requests
session = requests.Session()
session.headers["Authorization"] = f"Bearer {os.environ['REVISED_API_KEY']}"
UNIVERSITIES = ["Cornell University", "Harvard University", "Stanford University", "Yale University"]
GOVERNMENT = ["United Nations", "World Health Organization", "FCC"]
page = session.get(
"https://getrevised.com/api/v1/domains",
params={
"source": ",".join(UNIVERSITIES + GOVERNMENT),
"tier": "open",
"spam": "low",
"limit": 250,
},
timeout=30,
).json()
for row in page["data"]:
print(row["domain"], row["referring_domains"], row["linked_by"])
```
`requests` percent-encodes the spaces for you. There is no API endpoint that lists the catalogue, and no single value that means "every university". To see which names occur, read `linked_by` off a page of results, or browse the website's [.edu](https://getrevised.com/market/domains/source/edu) and [.gov](https://getrevised.com/market/domains/source/gov) hubs, which group the same sources.
A name the API cannot read is refused with `400 invalid_request`, not silently dropped — see [Comma-separated lists](/docs/api/filters#comma-separated-lists).
## What comes back
Open-tier listings with named academic, government or Wikipedia links, as of 23 September 2026:
| `domain` | `linked_by` | `referring_domains` | `snapshots` | `age_years` |
| --- | --- | --- | --- | --- |
| horriblevacuum.com | Cornell University, United Nations | `10-50` | `50+` | 11 |
| isrsireland.com | Cornell University, United Nations | `10-50` | `<10` | null |
| brettinternationalsports.com | Wikipedia | `50-100` | `<10` | 8 |
| levelupliterature.com | Wikipedia | `100-250` | `<10` | 6 |
Three things to notice:
- **Small referring-domain counts are normal here.** `horriblevacuum.com` has 10 to 50 referring domains, and two of them are Cornell and the UN. That is the pattern this filter exists to find.
- **`snapshots` says whether there was a real site.** `50+` archived copies is strong evidence of a site that existed and was maintained; `<10` is thin, so read the archive before trusting the links.
- **`null` age is unknown, not new.** Do not add `ageMin` to this query unless you mean to drop every row whose age Revised could not establish.
## Check the links before you act
A named link recorded in a crawl is evidence, not a guarantee.
Find the page on the linking site and check it still links to the name. Pages on large sites are moved, rewritten and archived; a university link from 2014 may be on a page that no longer exists.
A Wikipedia citation to a defunct company's press page is a different asset from one to a reference resource. The archive shows what the page was.
Links from a health agency to a health resource carry their value only if what you build is related. See [Have a plan for the content](/docs/guides/evaluating-a-domain#before-you-register-anything).
Background reading in the knowledge base: [Wikipedia backlinks](https://getrevised.com/knowledge/seo-fundamentals/wikipedia-backlinks) and [.edu and .gov backlinks](https://getrevised.com/knowledge/seo-fundamentals/edu-gov-backlinks).
## Over MCP
The MCP `search_domains` tool has no `source` argument. Ask your agent to search structurally, then read `linked_by` with `get_domain` on the survivors:
> Search open-tier listings with a low spam band, sorted by referring domains, then get the full record for the top ten and tell me which have a university or government site in `linked_by`.
## Next
Weigh named linkers against the rest of the row.
Where `linked_by` comes from, and every other field.