Finds journalists and media professionals on Twitter/X who cover a specific beat, industry, or topic. Journalists are the heaviest users of Twitter for professional networking — it's the best platform to build a media contact list.
Prerequisites
APIFY_TOKEN environment variable set- Optional: Apify MCP server installed
| Parameter | Type | Required | Default | Notes |
|---|
startUrls | array | Optional | [] | Twitter profile or tweet URLs |
twitterHandles | array | Optional | [] | Twitter usernames (without @) |
twitterUserIds | array | Optional | [] | Twitter user IDs |
getFollowers | boolean | Optional | false | Extract follower lists |
getFollowing | boolean | Optional | false | Extract following lists |
getRetweeters | boolean | Optional | false | Extract retweeters of a tweet URL |
includeUnavailableUsers | boolean | Optional | false | Include unavailable/suspended users |
maxItems | number | Optional | Unlimited | Maximum users to return |
customMapFunction | string | Optional | — | JavaScript function to transform each output object |
Workflow
Progress:
- [ ] Step 1: Define beat, industry, and target publications
- [ ] Step 2: Search for journalists tweeting about the beat
- [ ] Step 3: Enrich profiles to extract publication affiliation
- [ ] Step 4: Filter and verify journalist signals
- [ ] Step 5: Deliver press contact list
Step 1: Clarify Parameters
Ask the user for:
- Beat/topic (e.g., "artificial intelligence", "climate tech", "fintech", "B2B SaaS")
- Target publications (optional — e.g., "TechCrunch", "Forbes", "Wired", "any tier-1 tech media")
- Type — staff writers, freelancers, or both
- Geography (optional — US, UK, global)
- List size (default: 30 contacts)
Find journalists actively tweeting about the beat — recency of coverage matters for outreach.
Recommended — run_actor.js (handles waiting, output, and file saving automatically):
# Quick answer (prints table to chat)
node scripts/run_actor.js \
--actor "apidojo~twitter-user-scraper" \
--input '{"param": "value"}'
# Save as CSV
node scripts/run_actor.js \
--actor "apidojo~twitter-user-scraper" \
--input '{"param": "value"}' \
--output YYYY-MM-DD_results.csv --format csv
# Save as JSON
node scripts/run_actor.js \
--actor "apidojo~twitter-user-scraper" \
--input '{"param": "value"}' \
--output YYYY-MM-DD_results.json --format json
APIFY_TOKEN must be set in environment or .env file.
If Apify MCP is available:
Tool: apify:run-actor
Actor: "apidojo~tweet-scraper"
Input:
{
"searchTerms": [
"[TOPIC] journalist",
"[TOPIC] reporter",
"writing about [TOPIC]",
"[TOPIC] story [current year]"
],
"maxItems": 300,
"tweetLanguage": "en"
}
Also run a second query for article link tweets (journalists tweet their published work):
Input:
{
"searchTerms": ["[TOPIC] [publication_domain OR article link signal]"],
"maxItems": 200
}
REST API fallback:
curl -X POST \
"https://api.apify.com/v2/acts/apidojo~tweet-scraper/runs?token=$APIFY_TOKEN" \
-H "Content-Type: application/json" \
-d '{
"searchTerms": ["[TOPIC] journalist", "[TOPIC] reporter", "writing about [TOPIC]"],
"maxItems": 300
}'
Collect unique author usernames from all results.
Step 3: Enrich Profiles
If Apify MCP is available:
Tool: apify:run-actor
Actor: "apidojo~twitter-user-scraper"
Input:
{
"usernames": ["[username1]", "...", "up to 150 usernames"]
}
REST API fallback:
curl -X POST \
"https://api.apify.com/v2/acts/apidojo~twitter-user-scraper/runs?token=$APIFY_TOKEN" \
-H "Content-Type: application/json" \
-d '{"usernames": ["[username1]", "[username2]"]}'
Step 4: Filter for Journalist Signals
Keep accounts where bio contains ANY of:
- Publication names (e.g., "TechCrunch", "@Forbes", "Bloomberg", "@Wired")
- Journalist titles: "reporter", "journalist", "editor", "correspondent", "writer at", "staff writer", "freelance writer", "contributing editor"
- Byline signals: "bylines at", "writes for", "covering"
- Press credentials: "press", "media"
Follower range: 1,000–500,000 (removes complete unknowns and major TV anchors who don't respond to pitches)
Remove: PR/comms people (bio says "PR", "communications", "agency"), brand accounts, academics without journalist credentials.
# Journalist Outreach List: [BEAT/TOPIC]
Contacts found: [N] | Publication filter: [if any] | Date: [DATE]
## Contact List
| # | Name | @Handle | Publication | Beat | Followers | Recent Coverage |
|---|------|---------|-------------|------|-----------|-----------------|
| 1 | [name] | @[handle] | [pub] | [beat] | [N] | [recent tweet/article topic] |
## By Publication
### [Publication Name] ([N] contacts)
1. **[Name]** (@[handle]) — [title from bio] | [N] followers
Recent tweet: "[excerpt showing beat relevance]"
2. **[Name]** (@[handle]) — [title] | [N] followers
### Freelancers / Independent ([N] contacts)
1. **[Name]** (@[handle]) — writes for [pubs mentioned in bio] | [N] followers
## Pitch Angle Notes
Based on recent tweets, the top 5 contacts are actively covering:
1. @[handle]: recently tweeted about [specific topic] — pitch angle: [suggestion]
2. @[handle]: covering [topic] — pitch angle: [suggestion]
Personalization Tip
Before pitching, read the journalist's last 3 tweets and their most recent published article. Reference something specific. Generic pitches fail. The recent tweet data in this output enables that personalization without additional research.
Troubleshooting
Too many non-journalists in results: Strengthen bio filter — require "reporter" OR "journalist" OR "editor" as exact words, not just a publication name.
Can't find journalists for obscure beats: Widen the search to adjacent beats or try the publication name directly as a search term.
Follower counts seem stale: For final outreach list, spot-check the top 10 contacts directly on Twitter.