Find tweets similar to any given tweet using Twitter's own recommendation engine. Expand your research, discover related content, and map topic clusters.
Average response time: 110ms
const response = await fetch(
'https://scrapebadger.com/v1/twitter/tweets/tweet/1234567890/similar',
{ headers: { 'x-api-key': 'YOUR_API_KEY' } }
);
const similar = await response.json();
similar.data.forEach(t => console.log(t.text.substring(0, 80)));{
"data": [
{ "id": "555", "text": "We also just launched something similar...", "favorite_count": 89 },
{ "id": "666", "text": "Here's our take on this feature...", "favorite_count": 234 }
]
}/v1/twitter/tweets/tweet/{tweet_id}/similar| Parameter | Type | Required | Description |
|---|---|---|---|
tweet_id | string | Required | The tweet ID to find similar content for |
Aggregate top-performing content by topic or industry to fuel newsletters, social feeds, and content marketing calendars.
Collect large-scale Twitter datasets for computational social science, NLP research, political analysis, and network studies.
Detect emerging trends, viral content, and breaking news before they peak using real-time trending topic data.
Analyze consumer conversations, product feedback, and market trends to inform product development and go-to-market strategies.
Track how news stories propagate on Twitter, measure story amplification, and identify key distributors of information.
Monitor brand mentions, keywords, and conversations across Twitter in real time to understand public sentiment and emerging topics.
Twitter uses its internal recommendation algorithm based on content, engagement patterns, author similarity, and topic clustering.
The endpoint returns Twitter's default set of similar tweets, typically 10-20 results per request.
No. Similar tweets come from different authors. The algorithm finds content-similar tweets across all of Twitter.
Yes. Feed a competitor's popular tweet to find what others are saying about the same topic.
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