Scraping Tweets by Keyword

Raw tweet collection for any keyword, hashtag, or boolean search query. No assumed use case — returns the full tweet dataset for downstream analysis.

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: Build search query string
- [ ] Step 2: Run tweet-scraper
- [ ] Step 3: Poll for SUCCEEDED
- [ ] Step 4: Fetch and deliver dataset

Step 1: Build Search Query

Hashtag search → #keyword
Exact phrase → "exact phrase"
Boolean → word1 AND word2 -exclude
From account → from:username
Mention → @username

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": ["<query>"],
  "maxItems": 200,
  "since": "<YYYY-MM-DD>",
  "lang": "<lang_code>"
}

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": ["<query>"], "maxItems": 200}'

Save id as RUN_ID. Poll until status = SUCCEEDED:

curl "https://api.apify.com/v2/actor-runs/$RUN_ID?token=$APIFY_TOKEN" | grep '"status"'

Fetch results:

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

Step 3: Handle Edge Cases

0 results: Query may be too narrow, misspelled, or language-filtered. Broaden term, remove language filter, extend date range.
< 20 results: Try removing since/until constraints. Some low-volume terms have sparse data.
Duplicate tweet IDs: Deduplicate by id field before delivering.
Suspended/deleted accounts: Tweets from suspended accounts return with empty author fields — flag these rows.

Output Format

# Tweet Dataset: "<query>"
Total collected: N | Date range: SINCE – UNTIL | Language: LANG

| Tweet ID | Author | Text (truncated) | Likes | Retweets | Replies | Timestamp |
|----------|--------|-----------------|-------|----------|---------|-----------|
| ...      | ...    | ...             | ...   | ...      | ...     | ...       |

Full dataset: N rows × 15 fields
Available fields: id, text, author_id, author_username, likeCount, retweetCount,
replyCount, quoteCount, lang, createdAt, tweetUrl, media, isRetweet, isQuote, source

Troubleshooting

Empty results for a valid hashtag: Twitter API indexing lag — try again after 15 minutes. Rate limit error: Reduce maxItems to 100 and retry. Timeout on large requests: Set maxItems: 500 max per run; chain multiple runs with date ranges for larger datasets.

scraping-tweets-by-keyword