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Monitoring mentions is the cornerstone of Brand Reputation Management, Customer Support, and Competitor Analysis. While a general keyword search can be noisy, the /mentions endpoint is specifically tuned to find every time a particular handle is tagged or talked about on X.

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💡 Why Monitor Mentions?

  • Brand Protection: Get alerted to negative feedback or viral complaints before they escalate into a PR crisis.
  • Customer Support: Identify users asking for help or reporting bugs directly to your handle.
  • Community Engagement: Find your most loyal advocates who regularly tag you in their content.
  • Influencer Tracking: See which high-authority accounts are mentioning your competitors to identify potential partnership opportunities.
  • Viral Content Discovery: Filter mentions by engagement to find the most impactful conversations happening around a specific personality or brand.

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📥 Request Parameters

The /mentions endpoint is a specialized POST request that allows you to apply high-level filters directly in the query.
ParameterTypeDescription
querystringRequired. The username (handle) you want to track (e.g., elonmusk).
orderstringOptional. Sort results by latest (default) or popular.
since_datestringOptional. Start date in YYYY-MM-DD format.
until_datestringOptional. End date in YYYY-MM-DD format.
min_likesintegerOptional. Only show mentions with at least X likes.
min_retweetsintegerOptional. Only show mentions with at least X retweets.
min_repliesintegerOptional. Only show mentions with at least X replies.
next_cursorstringOptional. Cursor for pagination.

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🛠 Implementation Example

Using these filters allows you to ignore “noise” (like low-effort tags) and focus only on mentions that actually have reach and impact.

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cURL

Bash 
curl --request POST \
  --url https://api.sorsa.io/v3/mentions \
  --header 'ApiKey: <api-key>' \
  --header 'Content-Type: application/json' \
  --data '{
  "query": "elonmusk",
  "order": "popular",
  "min_likes": 100,
  "since_date": "2026-01-01",
  "until_date": "2026-02-01"
}'

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Python

Python 
import requests

url = "https://api.sorsa.io/v3/mentions"
headers = {
    "ApiKey": "YOUR_API_KEY",
    "Content-Type": "application/json"
}

payload = {
    "query": "AppleSupport",
    "order": "latest",
    "min_likes": 10,
    "since_date": "2026-02-01"
}

response = requests.post(url, json=payload, headers=headers)
mentions = response.json().get('tweets', [])

for tweet in mentions:
    print(f"New mention from @{tweet['user']['username']}: {tweet['full_text']}")

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🎯 Pro-Tips for Mention Tracking

  • Quality over Quantity: If you are a large brand, use min_likes to filter out spam or low-authority mentions. This ensures your team only sees posts that are actually being seen by others.
  • Crisis Management: Set order to latest and poll the endpoint frequently to catch urgent customer issues as they happen.
  • Historical Audits: Use since_date and until_date to pull reports on mention volume during a specific marketing campaign or product launch.

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⏭ Next Steps