Naver Search Trend API
Scrape Naver Search Trend data with one API call. Returns a relative search-interest time series for up to 5 Korean keywords from Naver Data Lab, under `data.results[].data[]` as `{period, ratio}` pairs. This is Korea's equivalent of Google Trends, and for the Korean market it is the more meaningful signal because Naver carries the majority of Korean search. IMPORTANT: `ratio` is a RELATIVE index scaled 0-100 within the window you requested, not an absolute search count, so values are not comparable between two different requests. History starts 2016-01-01; an earlier `start_date` is clamped up to it. A keyword with no measurable volume returns no data points and is not charged.
Last updated August 2026Maintained by the SocialCrawl team
Returns a search-interest time series for up to 5 Korean keywords as `results[].data[]` `{period, ratio}` pairs. `ratio` is a 0-100 index scoped to your window, not a search count.
Use it for Korean search demand over time, the Naver equivalent of Google Trends. For the Korean market it beats Google Trends because Naver carries most Korean search.
Searching 46 platforms in parallel
TikTok·
Instagram·
YouTube·
Facebook·
X·
LinkedIn·
Reddit·
Threads·
Pinterest·
Twitch·
Truth Social·
Snapchat·
Kick·
Bluesky·
Kwai·
Rumble·
Spotify·TikTok Shop·
Amazon Shop·
Google Shopping·
Trustpilot·
TripAdvisor·
Linktree·
Komi·
Pillar·
lnk.bio·Facebook Ads·Google Ads·LinkedIn Ads·Google Search·Google News·Google Finance·
Polymarket·
Tavily·
Hacker News·
GitHub·
Perplexity·
Naver·Utility·
Universal SearchTikTok·Instagram·YouTube·Facebook·X·LinkedIn·Reddit·Threads·Pinterest·Twitch·Truth Social·Snapchat·Kick·Bluesky·Kwai·Rumble·Spotify·TikTok Shop·Amazon Shop·Google Shopping·Trustpilot·TripAdvisor·Linktree·Komi·Pillar·lnk.bio·Facebook Ads·Google Ads·LinkedIn Ads·Google Search·Google News·Google Finance·Polymarket·Tavily·Hacker News·GitHub·Perplexity·Naver·Utility·Universal SearchTikTok·Instagram·YouTube·Facebook·X·LinkedIn·Reddit·Threads·Pinterest·Twitch·Truth Social·Snapchat·Kick·Bluesky·Kwai·Rumble·Spotify·TikTok Shop·Amazon Shop·Google Shopping·Trustpilot·TripAdvisor·Linktree·Komi·Pillar·lnk.bio·Facebook Ads·Google Ads·LinkedIn Ads·Google Search·Google News·Google Finance·Polymarket·Tavily·Hacker News·GitHub·Perplexity·Naver·Utility·Universal SearchTikTok·Instagram·YouTube·Facebook·X·LinkedIn·Reddit·Threads·Pinterest·Twitch·Truth Social·Snapchat·Kick·Bluesky·Kwai·Rumble·Spotify·TikTok Shop·Amazon Shop·Google Shopping·Trustpilot·TripAdvisor·Linktree·Komi·Pillar·lnk.bio·Facebook Ads·Google Ads·LinkedIn Ads·Google Search·Google News·Google Finance·Polymarket·Tavily·Hacker News·GitHub·Perplexity·Naver·Utility·Universal SearchWhat can you do with the Search Trend API?
The Search Trend endpoint gives you structured Naver 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/naver/search-trend?keywords=%EC%82%BC%EC%84%B1%EC%A0%84%EC%9E%90%2C%EA%B0%A4%EB%9F%AD%EC%8B%9C"import requests
response = requests.get(
"https://www.socialcrawl.dev/v1/naver/search-trend",
params={
'keywords': '삼성전자,갤럭시',
},
headers={"x-api-key": "YOUR_API_KEY"},
)
data = response.json()const response = await fetch(
"https://www.socialcrawl.dev/v1/naver/search-trend?keywords=%EC%82%BC%EC%84%B1%EC%A0%84%EC%9E%90%2C%EA%B0%A4%EB%9F%AD%EC%8B%9C",
{
headers: { "x-api-key": "YOUR_API_KEY" },
},
);
const data = await response.json();Parameters
| Parameter | Required | Description |
|---|---|---|
| keywords | Yes | Comma-separated Korean keywords, up to 5, combined into ONE trend series. Required. |
| start_date | No | Window start, `YYYY-MM-DD`. Defaults to 12 months before `end_date`. Clamped up to 2016-01-01, the earliest data Naver holds. |
| end_date | No | Window end, `YYYY-MM-DD`. Defaults to today. |
| time_unit | No | Aggregation bucket: `date`, `week`, or `month` (default `month`). (date | week | month) |
| group_name | No | Label for the series in the response. Defaults to the first keyword. |
| device | No | Restrict to `pc` or `mo` (mobile). Omit for both. (pc | mo) |
| gender | No | Restrict to `f` or `m`. Omit for both. (f | m) |
| ages | No | Comma-separated age-band codes, `0` to `11` (Naver's eleven bands, finest at the young end). NOTE this endpoint uses different codes from `shopping-insight/*`, which takes 10/20/30/40/50/60. |
What does the Naver Search Trend 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 Naver Search Trend response has the same fields.
How does the Naver Search Trend 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 46 platforms covering 10B+ monthly active users.
One schema, every platform
Query 46 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"
}
}
}Ready to scrape Naver Search Trend data?
Get your API key and start pulling Naver data in under 60 seconds.