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.
Last updated July 2026Maintained by the SocialCrawl team
Searching 44 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
curl -H "x-api-key: YOUR_API_KEY" \
"https://www.socialcrawl.dev/v1/content_analysis/phrase-trends?keyword=openai&date_from=2025-01-01"import requests
response = requests.get(
"https://www.socialcrawl.dev/v1/content_analysis/phrase-trends",
params={
'keyword': 'openai',
'date_from': '2025-01-01',
},
headers={"x-api-key": "YOUR_API_KEY"},
)
data = response.json()const response = await fetch(
"https://www.socialcrawl.dev/v1/content_analysis/phrase-trends?keyword=openai&date_from=2025-01-01",
{
headers: { "x-api-key": "YOUR_API_KEY" },
},
);
const data = await response.json();Parameters
| 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). |
What does the Content Analysis Phrase Trends API return?
Every response follows one unified schema. Here is a real, unmodified response body, so you can see the exact fields you get back before spending a credit.
Example response
{
"success": true,
"platform": "instagram",
"endpoint": "/v1/instagram/engagement",
"data": {
"engagement_rate_percentages": 38.33,
"recent_posts": 12,
"followers": 87608035,
"comments": 528912,
"likes": 33049046,
"recent_posts_explanation": "Statistics based on the last 12 posts",
"id_user": "2278169415",
"username": "mrbeast",
"is_private": false,
"posts_details": [
{
"likes": 5636982,
"comments": 69484,
"taken_at": 1781457954,
"datetime": "2026-06-14 20:25:54",
"hours_since_post": 461,
"time_ago": "19 days ago",
"likes_per_hour": 12228,
"comments_per_hour": 151
},
{
"likes": 20000768,
"comments": 223510,
"taken_at": 1732824650,
"datetime": "2024-11-28 23:10:50",
"hours_since_post": 13971,
"time_ago": "2 years ago",
"likes_per_hour": 1432,
"comments_per_hour": 16
},
{
"likes": 929226,
"comments": 30633,
"taken_at": 1782232475,
"datetime": "2026-06-23 19:34:35",
"hours_since_post": 246,
"time_ago": "10 days ago",
"likes_per_hour": 3777,
"comments_per_hour": 125
},
{
"likes": 487761,
"comments": 22482,
"taken_at": 1781799425,
"datetime": "2026-06-18 19:17:05",
"hours_since_post": 366,
"time_ago": "15 days ago",
"likes_per_hour": 1333,
"comments_per_hour": 61
},
{
"likes": 712265,
"comments": 15716,
"taken_at": 1781366405,
"datetime": "2026-06-13 19:00:05",
"hours_since_post": 487,
"time_ago": "20 days ago",
"likes_per_hour": 1463,
"comments_per_hour": 32
},
{
"likes": 1475116,
"comments": 35386,
"taken_at": 1781277094,
"datetime": "2026-06-12 18:11:34",
"hours_since_post": 512,
"time_ago": "21 days ago",
"likes_per_hour": 2881,
"comments_per_hour": 69
},
{
"likes": 1108220,
"comments": 26632,
"taken_at": 1780160249,
"datetime": "2026-05-30 19:57:29",
"hours_since_post": 822,
"time_ago": "1 months ago",
"likes_per_hour": 1348,
"comments_per_hour": 32
},
{
"likes": 542948,
"comments": 28476,
"taken_at": 1779375582,
"datetime": "2026-05-21 17:59:42",
"hours_since_post": 1040,
"time_ago": "1 months ago",
"likes_per_hour": 522,
"comments_per_hour": 27
},
{
"likes": 698514,
"comments": 24401,
"taken_at": 1779120014,
"datetime": "2026-05-18 19:00:14",
"hours_since_post": 1111,
"time_ago": "2 months ago",
"likes_per_hour": 629,
"comments_per_hour": 22
},
{
"likes": 468000,
"comments": 13548,
"taken_at": 1778947209,
"datetime": "2026-05-16 19:00:09",
"hours_since_post": 1159,
"time_ago": "2 months ago",
"likes_per_hour": 404,
"comments_per_hour": 12
},
{
"likes": 526594,
"comments": 24411,
"taken_at": 1777737719,
"datetime": "2026-05-02 19:01:59",
"hours_since_post": 1495,
"time_ago": "2 months ago",
"likes_per_hour": 352,
"comments_per_hour": 16
},
{
"likes": 462652,
"comments": 14233,
"taken_at": 1777580305,
"datetime": "2026-04-30 23:18:25",
"hours_since_post": 1538,
"time_ago": "2 months ago",
"likes_per_hour": 301,
"comments_per_hour": 9
}
]
},
"credits_used": 5,
"credits_remaining": 9999,
"request_id": "req_example000000",
"cached": false
}Example captured from the Instagram API. Every SocialCrawl endpoint returns this same unified schema, so your Content Analysis Phrase Trends response has the same fields.
How does the Content Analysis Phrase Trends API work?
Send a GET request with your API key and get back clean, structured JSON in our unified schema. Supported computed fields are populated when the source provides the required inputs.
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 44 platforms covering 10B+ monthly active users.
One schema, every platform
Query 44 platforms with identical response structures. Write your integration once.
Computed fields, not just scraped
When an endpoint supports these metrics and the source provides the required inputs, the normalized record includes engagement_rate, estimated_reach, content_category, and language — ready to use.
See your data before you code
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
Find answers to frequently asked questions about SocialCrawl's API, pricing, and capabilities.
Contact usHow do I track brand mentions over time with an API?
What parameters does phrase-trends take?
Can I see sentiment change, not just volume?
How is phrase-trends different from category-trends?
How much does the phrase trends API cost?
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