---name: tracking-hiring-signals-from-company-tweetsdescription: >scraper on Apify. Triggers when the user asks to: find companies that are actively hiring onlicense: Apache-2.0metadata: author: apidojoversion: 1.0apify-actor: apidojo/tweet-scraper---

Tracking Hiring Signals from Company Tweets

Monitors company Twitter accounts for hiring announcements and growth signals. Companies tweet about openings before jobs.page or LinkedIn posts go live — Twitter is an early signal channel.

Prerequisites

• APIFY_TOKEN environment variable set
• Optional: Apify MCP server installed

Inputs

Parameter	Type	Required	Default	Notes
searchTerms	array	✅	[]	Twitter advanced search queries (e.g. ["#AI lang:en", "from:NASA"])
sort	string	Optional	Top	Sort order: Latest, Top, or Latest+Top
tweetLanguage	string	Optional	—	ISO 639-1 language code (e.g. en)
maxItems	number	Optional	Unlimited	Maximum tweets to return
onlyVerifiedUsers	boolean	Optional	false	Only tweets from verified users
onlyTwitterBlue	boolean	Optional	false	Only Twitter Blue subscribers
onlyImage	boolean	Optional	false	Only tweets with images
onlyVideo	boolean	Optional	false	Only tweets with videos
onlyQuote	boolean	Optional	false	Only quote tweets
author	string	Optional	—	Filter to a specific author handle
inReplyTo	string	Optional	—	Tweets replying to a specific handle
mentioning	string	Optional	—	Tweets mentioning a specific handle
geotaggedNear	string	Optional	—	Tweets near a location
withinRadius	string	Optional	—	Radius around geotaggedNear
geocode	string	Optional	—	Lat/lng + radius string
placeObjectId	string	Optional	—	Tweets tagged with a place
minimumRetweets	number	Optional	—	Minimum retweet count
minimumFavorites	number	Optional	—	Minimum like count
minimumReplies	number	Optional	—	Minimum reply count
start	string	Optional	—	Tweets after this date (YYYY-MM-DD)
end	string	Optional	—	Tweets before this date (YYYY-MM-DD)
includeSearchTerms	boolean	Optional	false	Add the matched search term to each tweet
customMapFunction	string	Optional	—	JavaScript function to transform each output object

Workflow

Progress:
- [ ] Step 1: Search for hiring-signal tweets in sector
- [ ] Step 2: (Optional) Scrape specific company accounts
- [ ] Step 3: Extract role and team info from tweet text
- [ ] Step 4: Score growth signal strength
- [ ] Step 5: Deliver hiring intelligence report

Step 1: Search Hiring Signals

Recommended — run_actor.js (handles waiting, output, and file saving automatically):

# Quick answer (prints table to chat)
node scripts/run_actor.js \
  --actor "apidojo~tweet-scraper" \
  --input '{"param": "value"}'

# Save as CSV
node scripts/run_actor.js \
  --actor "apidojo~tweet-scraper" \
  --input '{"param": "value"}' \
  --output YYYY-MM-DD_results.csv --format csv

# Save as JSON
node scripts/run_actor.js \
  --actor "apidojo~tweet-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": ["we're hiring [SECTOR]", "join our team [SECTOR]", "[ROLE] hiring [SECTOR]"],
  "maxItems": 300
}

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": ["we are hiring fintech", "join our team SaaS startup", "software engineer hiring"],
    "maxItems": 300
  }'

Step 2: Extract Role Signals from Tweet Text

role_mentioned = extract noun phrases after "hiring a/an", "looking for a/an", "seeking a"
team_mentioned = extract from: "engineering team", "sales team", "marketing", "product team"
urgency = "immediately", "ASAP", "urgent" → HIGH; "growing team" → MEDIUM; general → LOW

Step 3: Growth Signal Score

hiring_signal_score = (is_confirmed_company_account ? 1 : 0.5) * 0.30
                    + (role_is_specific ? 1 : 0.5) * 0.25
                    + (post_is_recent: ≤7 days = 1, 8-14 = 0.7, 15-30 = 0.4) * 0.25
                    + (link_to_job_page ? 1 : 0) * 0.20

Growth tier: Multiple hiring tweets in 30 days = HIGH_GROWTH; 1-2 = STEADY_HIRE; no link = SIGNAL_ONLY

Step 4: Edge Cases

• Retweets from employee accounts: If a company employee retweets a job post, keep — it's still a valid signal; note it's not the company's official account
• Job boards posting on behalf of company: Filter out accounts named "JobsAt[Company]", staffing agencies, or accounts posting > 10 hiring tweets/day (aggregators)
• Role extraction fails: Note the tweet verbatim and mark role = "unspecified" — still a growth signal
• Same company posts 5 roles: Deduplicate by author.username; count unique companies, not unique tweets

Output Format

# Hiring Signal Intelligence: [SECTOR/ROLE]
Tweets analyzed: [N] | Companies with hiring signals: [N] | Date: [DATE]

## High-Growth Companies (Multiple Roles Posted)
| Company | @Handle | Roles Mentioned | Teams | Posts | Link to Jobs | Score |
|---------|---------|----------------|-------|-------|-------------|-------|
| [name] | @[handle] | [role list] | [eng/mktg] | [N] | [Yes/No] | [0.XX] |

## Single Hire Signals
| Company | @Handle | Role | Team | Tweet Date | Job Link |
|---------|---------|------|------|-----------|---------|

## Role Distribution Across All Companies
| Role Category | # Companies Hiring | Urgency |
|--------------|-------------------|---------|
| Engineering | [N] | [High/Med] |
| Marketing | [N] | |
| Sales | [N] | |

Troubleshooting

Results dominated by job boards: Add negative terms to search: -jobs -jobboard -staffing -recruiting Sector too broad: Narrow with a sub-sector or specific stage: "Series A fintech" instead of "fintech". Job links are broken/expired: Hiring tweets are posted in real-time; check within 48h for best link validity.