scraping-tweets-by-keyword

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.