Content Analysis Phrase Trends API
Scrape Content Analysis Phrase Trends data with one API call. Returns a time series (one row per day/week/month bucket) of mention volume and sentiment for the keyword over a date range. Each row is a full summary sub-object (total_count, sentiment, top domains, categories…). Track how a brand's web-wide mentions and sentiment move over time.
Try the Content Analysis Phrase Trends API
See real data before writing a single line
Searching 35 platforms in parallel
What can you do with the Phrase Trends API?
The Phrase Trends endpoint gives you structured Content Analysis data with computed fields in a single request. No scraping infrastructure to build or maintain.
Example Request
GET /v1/content_analysis/phrase-trends?keyword=openai&date_from=2025-01-01Parameters
| Parameter | Required | Description |
|---|---|---|
| keyword | Yes | Brand or term to trend. |
| date_from | Yes | Start of the date range (yyyy-mm-dd). |
| date_to | No | End of the date range (yyyy-mm-dd); defaults to today. |
| date_group | No | Bucket size: day, week, or month (default month). (day | week | month) |
| page_type | No | Narrow to one or more page types (comma-separated): ecommerce, news, blogs, message-boards, organization. (ecommerce | news | blogs | message-boards | organization) |
| internal_list_limit | No | Cap on internal arrays per bucket (1–20). |
| filters | No | Advanced DataForSEO filter expression as a JSON array (≤8 conditions). |
How does the Content Analysis Phrase Trends API work?
Send a GET request with your API key and get back clean, structured JSON. Every response follows our unified schema with computed fields.
Method
GET
Response
JSON
How do you scrape social media data in seconds?
The fastest social media scraping API for developers. Scrape profiles, posts, comments, and analytics from 35 platforms covering 10B+ monthly active users.
One schema, every platform
Query 35 platforms with identical response structures. Write your integration once.
Computed fields, not just scraped
Every response includes engagement_rate, estimated_reach, content_category, and language — ready to use.
No code required
Visual Data Explorer — paste any URL, get rich result cards, sortable tables, CSV export.
import requests
response = requests.get(
'https://www.socialcrawl.dev/v1/tiktok/profile',
params={'handle': 'charlidamelio'},
headers={'x-api-key': 'sc_YOUR_API_KEY'}
)
data = response.json(){
"success": true,
"platform": "tiktok",
"data": {
"author": {
"username": "charlidamelio",
"followers": 152400000
},
"engagement": {
"likes": 12400000000,
"engagement_rate": 0.087
},
"metadata": {
"language": "en",
"content_category": "lifestyle"
}
}
}Have a question? We got answers
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