datagrit › Data › Medium Publication Finder: Subscribers & Activity

Medium Publication Finder: Subscribers & Activity

Find Medium publications by keyword and score each one: subscribers, posting cadence, claps per post, paywalled share and top authors.

Medium Publication Finder turns a keyword (or a list of publication names) into one scorecard row per Medium publication: how many people follow it, how often it posts, when it last posted, how many claps a typical story gets, how much of it sits behind the paywall, and who writes for it.

It reads the public data Medium serves to any visitor, so there is no login, no API key and no Medium account involved. Export the rows as JSON, CSV or Excel, call the Actor through the Apify API, or connect it to n8n, Make and AI agents through MCP.

Why use Medium Publication Finder?

Medium search lists publications by relevance and shows nothing about whether they are alive. This Actor adds the part you need to decide where to spend time: cadence and engagement computed from the latest 25 posts of each publication.

• Build a pitch list. Search a topic, keep publications with a few hundred to a few thousand followers that posted this month, and rank them by claps per 1,000 subscribers.
• Drop dormant giants. A publication with 800,000 followers and no post for a year is a bad target. Set "Posted within the last (days)" and it disappears.
• Benchmark competitors and sponsors. Compare posts per week, median claps, responses and member-only share across a shortlist of publications in your niche.
• Find the editors. Each row carries the creator, the editors and the most frequent authors with their usernames.
• Feed dashboards and agents. One flat row per publication, stable field names, no article dumps to post-process.

Output fields

Each row has the publication identity (id, slug, name, url, customDomain, tagline, description), people (creatorUsername, creatorName, editorsCount, editors, twitterUsername, newsletterSlug), size (subscribers), cadence (postsSampled, sampleSpanDays, lastPostAt, daysSinceLastPost, postsPerWeek, activityStatus), engagement (medianClaps, averageClaps, medianClapsPer1kSubscribers, medianResponses), content (medianReadingMinutes, medianWords, memberOnlySharePct, distinctAuthors, topAuthors, topTags, bestPost) and the run context (query, found, sourceUrl, scrapedAt).

When nothing can be returned for an input you get one row with found: false, a reason and a message: noMatches (the keyword found no publications), filteredOut (publications were found but none passed your filters), notFound (no such slug or domain) or fetchFailed (Medium did not answer after retries).

How the metrics are computed

Medium serves at most 25 recent posts per publication, so all cadence and engagement figures describe that sample. postsPerWeek is the number of sampled posts divided by the time between the oldest sampled post and now, and sampleSpanDays tells you how long that window is. activityStatus is active when the newest post is at most 14 days old, slowing up to 60 days and dormant beyond that. medianClapsPer1kSubscribers divides the median claps of the sample by followers, which makes small and large publications comparable.

Limits

• The sample is the latest 25 posts; the Actor cannot page further back.
• Medium does not publish submission guidelines or acceptance rates, so the rows do not say whether a publication takes pitches. They tell you whether it is alive and how its stories perform.
• Clap counts are Medium's public totals and can be zero for publications whose readers rarely clap.
• Subscriber counts are Medium's follower numbers at the time of the run.

Is it legal to scrape Medium publications?

The Actor reads only public publication data that Medium serves to anyone without logging in. It does not read member-only story text, private data or anything behind a login, and it does not bypass access controls. You are responsible for using the data in line with applicable laws, including data protection rules, and Medium's terms. If you find an issue, open it in the Issues tab; problems are answered within one business day.

Output fields

Every result is one flat record, so it drops straight into a spreadsheet, a database or a CRM.

Sample record

{
  "query": "startup",
  "id": "f5af2b715248",
  "slug": "swlh",
  "name": "The Startup",
  "url": "https://medium.com/swlh",
  "customDomain": "uxdesign.cc",
  "tagline": "Get smarter at building your thing.",
  "description": "Get smarter at building your thing. Follow to join The Startup’s +8 million monthly readers.",
  "subscribers": 894499,
  "creatorUsername": "meseali",
  "creatorName": "Ali Mese",
  "editorsCount": 2,
  "editors": [
    {
      "username": "meseali",
      "name": "Ali Mese"
    }
  ],
  "twitterUsername": "GrowthSupply",
  "newsletterSlug": "top-stories",
  "postsSampled": 25,
  "sampleSpanDays": 175.3,
  "lastPostAt": "2026-05-25T19:56:00.532Z",
  "daysSinceLastPost": 134.6,
  "postsPerWeek": 1,
  "activityStatus": "dormant",
  "medianClaps": 412,
  "averageClaps": 380.5,
  "medianClapsPer1kSubscribers": 0.46,
  "medianResponses": 8,
  "medianReadingMinutes": 5.6,
  "medianWords": 1024,
  "memberOnlySharePct": 68,
  "distinctAuthors": 22,
  "topAuthors": [
    {
      "username": "aldric-chen",
      "name": "Aldric Chen",
      "posts": 3
    }
  ],
  "topTags": [
    {
      "tag": "productivity",
      "posts": 6
    }
  ],
  "bestPost": {
    "title": "These Countries Offer Real Estate Visas",
    "url": "https://medium.com/swlh/example-396cb0c83ba2",
    "claps": 474
  },
  "found": true,
  "reason": "filteredOut",
  "message": "Publications were found but none passed the subscriber and activity filters.",
  "sourceUrl": "https://medium.com/swlh",
  "scrapedAt": "2026-10-07T08:00:00.000Z"
}

Input

Call it from your code

Run the Actor and get the results in one request. Replace YOUR_APIFY_TOKEN with the token from your Apify account settings.

curl -X POST "https://api.apify.com/v2/acts/datagrit~medium-publication-finder/run-sync-get-dataset-items?token=YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"queries":["startup","machine learning"],"maxPublicationsPerQuery":8,"maxItems":16}'

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('datagrit/medium-publication-finder').call({
  "queries": [
    "startup",
    "machine learning"
  ],
  "maxPublicationsPerQuery": 8,
  "maxItems": 16
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items.length, items[0]);

from apify_client import ApifyClient
import os

client = ApifyClient(os.environ["APIFY_TOKEN"])
run = client.actor("datagrit/medium-publication-finder").call(run_input={
  "queries": [
    "startup",
    "machine learning"
  ],
  "maxPublicationsPerQuery": 8,
  "maxItems": 16
})
items = client.dataset(run["defaultDatasetId"]).list_items().items
print(len(items), items[0] if items else None)

Frequently asked questions

Guide

How to find active Medium publications and rank them by engagement — Find Medium publications by keyword and score each by followers, posting cadence, claps per 1,000 followers and paywalled share, in Python or cURL.

Related Actors