Get every tweet that mentions a specific user. Perfect for brand monitoring, customer feedback tracking, and reputation management.
Average response time: 100ms
const response = await fetch(
'https://scrapebadger.com/v1/twitter/users/scrapebadger/mentions',
{ headers: { 'x-api-key': 'YOUR_API_KEY' } }
);
const mentions = await response.json();
mentions.data.forEach(t => console.log(t.author.username, t.text));{
"data": [
{
"id": "mention_001",
"text": "@scrapebadger your API is amazing, just saved us hours!",
"author": { "username": "happy_user", "followers_count": 2300 },
"created_at": "2025-01-20T14:30:00Z"
}
],
"next_cursor": "mention_cursor"
}/v1/twitter/users/{username}/mentions| Parameter | Type | Required | Description |
|---|---|---|---|
username | string | Required | The username to find mentions for |
count | integer | Optional | Results per page (default: 20) |
cursor | string | Optional | Pagination cursor for next page |
Get alerts when your brand is mentioned, track share of voice, and respond quickly to customer feedback or PR crises.
Monitor brand mentions, keywords, and conversations across Twitter in real time to understand public sentiment and emerging topics.
Detect and track PR crises, service outages, and negative viral moments in real time to enable rapid response.
Feed tweet text into NLP pipelines to classify sentiment, detect emotions, and measure public opinion on products, events, or topics.
Track competitor accounts, engagement rates, and content strategies to benchmark performance and identify opportunities.
Manage Twitter communities by tracking member activity, top contributors, discussion themes, and community health metrics.
Yes. Any tweet that contains @username is included, whether it's a direct mention, reply, or quote tweet.
For real-time monitoring, combine this endpoint with ScrapeBadger Stream Monitors for instant webhook notifications.
Mentions are available for the last 7-10 days. For historical data, use the Advanced Search endpoint with "to:" operator.
The API returns raw mention data. Pipe the results through an NLP sentiment analysis service for classification.
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