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Tracking Startup Founders On Twitter
Executes tracking startup founders on twitter using apidojo scrapers. Part of the apidojo intelligence skills library.
Prerequisites
APIFY_TOKENenvironment variable set- Optional: Apify MCP server installed
Inputs
| 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 parameters
- [ ] Step 2: Run twitter-user-scraper
- [ ] Step 3: Filter and classify results
- [ ] Step 4: Score by quality and relevance
- [ ] Step 5: Deliver outputStep 2: Run the Actor
Recommended — run_actor.js (handles waiting, output, and file saving automatically):
bash
# 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 jsonAPIFY_TOKENmust be set in environment or.envfile.
If Apify MCP is available:
Tool: apify:run-actor
Actor: "apidojo~twitter-user-scraper"
Input:
{
"searchTerms": ["founder [SECTOR]", "building [SECTOR] startup", "CEO [SECTOR]", "#buildinpublic [SECTOR]"],
"maxItems": 100
}REST API fallback:
bash
curl -X POST \
"https://api.apify.com/v2/acts/apidojo~twitter-user-scraper/runs?token=$APIFY_TOKEN" \
-H "Content-Type: application/json" \
-d '{"searchTerms": ["founder [SECTOR]", "building [SECTOR] startup", "CEO [SECTOR]", "#buildinpublic [SECTOR]"], "maxItems": 100}'Wait for SUCCEEDED. Fetch dataset:
bash
curl "https://api.apify.com/v2/actor-runs/$RUN_ID/dataset/items?token=$APIFY_TOKEN"Step 3: Classify Results
classification: EARLY_STAGE (< 1K followers, building in public) | SEED_STAGE (1K-10K, active fundraising signals) | GROWTH_STAGE (> 10K, scaling)Step 4: Score Each Result
score = founder_signal_score = (bio_contains_founder_title ? 1 : 0) * 0.35 + (recent_product_tweet ? 1 : 0) * 0.35 + min(followerCount/10000, 1) * 0.30Step 5: Edge Cases
- Many 'founder' accounts are actually solopreneurs or side-project builders — not venture-backed; verify by looking for funding mentions or accelerator affiliations in bio
Additional fallbacks:
- < 20 results: Broaden search terms; remove secondary filters
- No results: Verify the search terms are correct; try alternate phrasings
- Data quality issues: Remove entries with missing key fields; note count in output
Output Format
# Tracking Startup Founders On Twitter
Results: [N] | Date: [DATE]
| # | [Key Field] | [Metric 1] | [Metric 2] | [Classification] | [Score] |
|---|------------|-----------|-----------|-----------------|---------|
| 1 | [value] | [value] | [value] | [type] | [0.XX] |
## Summary
Top result: [description]
Key finding: [insight]Troubleshooting
Too few results: Broaden the primary search term; remove restrictive filters. Low quality results: Apply minimum score threshold (≥ 0.50) to filter noise. Actor fails to run: Verify API key; check actor status at apify.com/apidojo.
