Monitoring Vc Investor Activity On Twitter

Monitors VC investor activity and deal signals on Twitter using apidojo's Tweet scraper. Triggers when the user asks to: monitor VC activity on Twitter, track what investors are tweeting about, find VCs who are actively investing in a sector on X, monitor deal flow signals from investor tweets, find investors who are looking for deals in a space, track funding announcements from VC firms on Twitter, or discover which investors are most active in a specific vertical. Returns investor handle, firm, investment thesis signals, recent activity, deal flow indicators. Ideal for startup founders fundraising, co-investors, and startup ecosystem analysts.

apidojo-io Updated Sep 17, 2026

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Monitoring Vc Investor Activity On Twitter

Executes monitoring vc investor activity on twitter using apidojo scrapers. Part of the apidojo intelligence skills library.

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: Define parameters
- [ ] Step 2: Run tweet-scraper
- [ ] Step 3: Filter and classify results
- [ ] Step 4: Score by quality and relevance
- [ ] Step 5: Deliver output

Step 2: Run the Actor

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": ["investing in [SECTOR]", "excited about [SECTOR]", "looking for [SECTOR] startups", "portfolio company [SECTOR]"],
  "maxItems": 100
}

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": ["investing in [SECTOR]", "excited about [SECTOR]", "looking for [SECTOR] startups", "portfolio company [SECTOR]"], "maxItems": 100}'

Wait for SUCCEEDED. Fetch dataset:

curl "https://api.apify.com/v2/actor-runs/$RUN_ID/dataset/items?token=$APIFY_TOKEN"

Step 3: Classify Results

classification: ACTIVE_INVESTOR (recent deal activity, thesis tweets) | PASSIVE_FOLLOWER (investor title but no deal signals) | ANGEL (individual, smaller checks) | FIRM_PARTNER (major VC firm affiliation)

Step 4: Score Each Result

score = deal_signal_score = (tweeted_investment_thesis ? 1 : 0) * 0.35 + (tweeted_about_portfolio ? 1 : 0) * 0.25 + (bio_contains_VC_firm ? 1 : 0) * 0.25 + (followerCount > 5000 ? 1 : 0.5) * 0.15

Step 5: Edge Cases

Distinguish actual investment partners from associates and VPs — partners make investment decisions; use title from bio for classification

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

# Monitoring Vc Investor Activity 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.

---name: monitoring-vc-investor-activity-on-twitterdescription: Monitors VC investor activity and deal signals on Twitter using apidojo's Tweet scraper. Triggers when the user asks to: monitor VC activity on Twitter, track what investors are tweeting about, find VCs who are actively investing in a sector on X, monitor deal flow signals from investor tweets, find investors who are looking for deals in a space, track funding announcements from VC firms on Twitter, or discover which investors are most active in a specific vertical. Returns investor handle, firm, investment thesis signals, recent activity, deal flow indicators. Ideal for startup founders fundraising, co-investors, and startup ecosystem analysts.license: Apache-2.0---# Monitoring Vc Investor Activity On TwitterExecutes monitoring vc investor activity on twitter using apidojo scrapers. Part of the apidojo intelligence skills library.## 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: Define parameters- [ ] Step 2: Run tweet-scraper- [ ] Step 3: Filter and classify results- [ ] Step 4: Score by quality and relevance- [ ] Step 5: Deliver output```### Step 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~tweet-scraper" \ --input '{"param": "value"}'# Save as CSVnode scripts/run_actor.js \ --actor "apidojo~tweet-scraper" \ --input '{"param": "value"}' \ --output YYYY-MM-DD_results.csv --format csv# Save as JSONnode 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-actorActor: "apidojo~tweet-scraper"Input:{ "searchTerms": ["investing in [SECTOR]", "excited about [SECTOR]", "looking for [SECTOR] startups", "portfolio company [SECTOR]"], "maxItems": 100}```**REST API fallback:**```bashcurl -X POST \ "https://api.apify.com/v2/acts/apidojo~tweet-scraper/runs?token=$APIFY_TOKEN" \ -H "Content-Type: application/json" \ -d '{"searchTerms": ["investing in [SECTOR]", "excited about [SECTOR]", "looking for [SECTOR] startups", "portfolio company [SECTOR]"], "maxItems": 100}'```Wait for `SUCCEEDED`. Fetch dataset:```bashcurl "https://api.apify.com/v2/actor-runs/$RUN_ID/dataset/items?token=$APIFY_TOKEN"```### Step 3: Classify Results```classification: ACTIVE_INVESTOR (recent deal activity, thesis tweets) | PASSIVE_FOLLOWER (investor title but no deal signals) | ANGEL (individual, smaller checks) | FIRM_PARTNER (major VC firm affiliation)```### Step 4: Score Each Result```score = deal_signal_score = (tweeted_investment_thesis ? 1 : 0) * 0.35 + (tweeted_about_portfolio ? 1 : 0) * 0.25 + (bio_contains_VC_firm ? 1 : 0) * 0.25 + (followerCount > 5000 ? 1 : 0.5) * 0.15```### Step 5: Edge Cases- **Distinguish actual investment partners from associates and VPs — partners make investment decisions; use title from bio for classification**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```# Monitoring Vc Investor Activity On TwitterResults: [N] | Date: [DATE]| # | [Key Field] | [Metric 1] | [Metric 2] | [Classification] | [Score] ||---|------------|-----------|-----------|-----------------|---------|| 1 | [value] | [value] | [value] | [type] | [0.XX] |## SummaryTop 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.

apidojo-io/apidojo-skills/tree/main/skills/intent/monitoring-vc-investor-activity-on-twitter commit f254557ace

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