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tracking-hiring-signals-from-company-tweets

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Tracks hiring signals and growth indicators from company Twitter accounts using apidojo's Tweet scraper on Apify. Triggers when the user asks to: find companies that are actively hiring on Twitter, track job posting announcements from company accounts on X, identify startups that are growing based on their hiring tweets, find companies hiring for specific roles from their Twitter, monitor competitor hiring activity on social media, discover which companies are expanding teams in a specific sector, or build a list of companies actively hiring for your skill set. Returns company handle, role being hired, team/department signal, post date, and growth indicator. Ideal for job seekers, talent intelligence teams, VCs tracking portfolio growth, and competitor analysts.

What it does

Tracks hiring signals and growth indicators from company Twitter accounts using apidojo's Tweet scraper on Apify. Triggers when the user asks to: find companies that are actively hiring on Twitter, track job posting announcements from company accounts on X, identify startups that are growing based on their hiring tweets, find companies hiring for specific roles from their Twitter, monitor competitor hiring activity on social media, discover which companies are expanding teams in a specific sector, or build a list of companies actively hiring for your skill set. Returns company handle, role being hired, team/department signal, post date, and growth indicator. Ideal for job seekers, talent intelligence teams, VCs tracking portfolio growth, and competitor analysts.

The skill document

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

ParameterTypeRequiredDefaultNotes
searchTermsarray[]Twitter advanced search queries (e.g. ["#AI lang:en", "from:NASA"])
sortstringOptionalTopSort order: Latest, Top, or Latest+Top
tweetLanguagestringOptionalISO 639-1 language code (e.g. en)
maxItemsnumberOptionalUnlimitedMaximum tweets to return
onlyVerifiedUsersbooleanOptionalfalseOnly tweets from verified users
onlyTwitterBluebooleanOptionalfalseOnly Twitter Blue subscribers
onlyImagebooleanOptionalfalseOnly tweets with images
onlyVideobooleanOptionalfalseOnly tweets with videos
onlyQuotebooleanOptionalfalseOnly quote tweets
authorstringOptionalFilter to a specific author handle
inReplyTostringOptionalTweets replying to a specific handle
mentioningstringOptionalTweets mentioning a specific handle
geotaggedNearstringOptionalTweets near a location
withinRadiusstringOptionalRadius around geotaggedNear
geocodestringOptionalLat/lng + radius string
placeObjectIdstringOptionalTweets tagged with a place
minimumRetweetsnumberOptionalMinimum retweet count
minimumFavoritesnumberOptionalMinimum like count
minimumRepliesnumberOptionalMinimum reply count
startstringOptionalTweets after this date (YYYY-MM-DD)
endstringOptionalTweets before this date (YYYY-MM-DD)
includeSearchTermsbooleanOptionalfalseAdd the matched search term to each tweet
customMapFunctionstringOptionalJavaScript 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.

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