Content Analysis Category Trends API
Scrape Content Analysis Category Trends data with one API call. Like phrase-trends, but keyed on a category code from the /content_analysis/categories taxonomy instead of a keyword. Returns a time series of mention volume and sentiment for an entire content category (e.g. Apparel) over a date range. Note the different mental model: this trends a category, not a brand term.
Try the Content Analysis Category Trends API
See real data before writing a single line
Searching 35 platforms in parallel
TikTok·
Instagram·
YouTube·
Facebook·
X·
LinkedIn·
Reddit·
Threads·
Pinterest·
Twitch·
Truth Social·
Snapchat·
Kick·
Bluesky·
Rumble·
Spotify·TikTok Shop·
Amazon Shop·
Google Shopping·
Trustpilot·
TripAdvisor·
Linktree·
Komi·
Pillar·
lnk.bio·Facebook Ads·Google Ads·LinkedIn Ads·Google Search·
Polymarket·
Tavily·
Hacker News·
GitHub·
Perplexity·
Naver·UUtility·
Universal SearchTikTok·Instagram·YouTube·Facebook·X·LinkedIn·Reddit·Threads·Pinterest·Twitch·Truth Social·Snapchat·Kick·Bluesky·Rumble·Spotify·TikTok Shop·Amazon Shop·Google Shopping·Trustpilot·TripAdvisor·Linktree·Komi·Pillar·lnk.bio·Facebook Ads·Google Ads·LinkedIn Ads·Google Search·Polymarket·Tavily·Hacker News·GitHub·Perplexity·Naver·UUtility·Universal SearchTikTok·Instagram·YouTube·Facebook·X·LinkedIn·Reddit·Threads·Pinterest·Twitch·Truth Social·Snapchat·Kick·Bluesky·Rumble·Spotify·TikTok Shop·Amazon Shop·Google Shopping·Trustpilot·TripAdvisor·Linktree·Komi·Pillar·lnk.bio·Facebook Ads·Google Ads·LinkedIn Ads·Google Search·Polymarket·Tavily·Hacker News·GitHub·Perplexity·Naver·UUtility·Universal SearchTikTok·Instagram·YouTube·Facebook·X·LinkedIn·Reddit·Threads·Pinterest·Twitch·Truth Social·Snapchat·Kick·Bluesky·Rumble·Spotify·TikTok Shop·Amazon Shop·Google Shopping·Trustpilot·TripAdvisor·Linktree·Komi·Pillar·lnk.bio·Facebook Ads·Google Ads·LinkedIn Ads·Google Search·Polymarket·Tavily·Hacker News·GitHub·Perplexity·Naver·UUtility·Universal SearchWhat can you do with the Category Trends API?
The Category 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/category-trends?category_code=10021&date_from=2025-01-01Parameters
| Parameter | Required | Description |
|---|---|---|
| category_code | Yes | Numeric category code from the /content_analysis/categories taxonomy (e.g. 10021 = Apparel). |
| 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) |
| 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 Category 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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