Track Naver News for Korean Industry Trends
Export Naver News results as JSON — outlet, headline, date, rank — to follow Korean industry coverage and announcements in your sector.
TL;DR — The Naver Scraper exports Naver News results — headline, outlet, date, rank — as JSON. Query your sector's Korean terms on a schedule and industry coverage becomes a structured feed instead of an unread bookmark folder.
Why Korean industry coverage starts on Naver
Korean industry news lives on Korean outlets, aggregated through Naver — the platform where the country's press is actually read. Regulatory announcements, conglomerate moves, startup funding — they break in Korean first, and English coverage lags or never arrives.
The job: a dated index of what Korean media published on your sector this week, per query, as data.
How does this compare to the alternatives?
| English trade press | Naver site browsing | Thirdwatch actor | |
|---|---|---|---|
| Cost | Free, lagged | Free, manual | Pay per result |
| Reliability | Partial coverage | Complete but tedious | Structured daily |
| Setup time | Zero | Language barrier | Minutes |
| Maintenance | Subscribe and wait | Habit | Scheduled runs |
How to track coverage in 4 steps
How do I pull the sector feed?
import os
from apify_client import ApifyClient
client = ApifyClient(os.environ["APIFY_TOKEN"])
run = client.actor("thirdwatch/naver-scraper").call(
run_input={
"queries": ["반도체 수출", "배터리 시장"],
"searchType": "news",
"sort": "recent",
"period": "week",
"maxResultsPerQuery": 50,
"proxyConfiguration": {"useApifyProxy": False},
}
)
rows = list(client.dataset(run["defaultDatasetId"]).iterate_items())How do I group by outlet?
import pandas as pd
df = pd.DataFrame(rows)
print(df.groupby("publisher").size().sort_values(ascending=False).head(15))Outlet concentration shows which media own the beat — useful for PR targeting too.
How do I dedupe to the new file?
Persist url across runs; new URLs are the week's coverage. published_label gives the relative freshness ("3일 전") at a glance.
How do I read what matters?
Rank the week's headlines by outlet authority, translate titles in bulk, and open the top URLs — the structured index makes triage a five-minute job.
Sample output
{"query": "반도체 수출", "search_type": "news", "rank": 3,
"title": "8월 반도체 수출 2개월 연속 증가…AI 수요 견인",
"url": "https://n.news.naver.com/article/001/0015643210",
"publisher": "연합뉴스", "published_label": "2일 전",
"result_source": "news", "is_sponsored": false}Common pitfalls
Industry queries need the Korean term — English equivalents reach only English-facing coverage. published_label is relative text; store run dates so "2일 전" stays interpretable. Naver's ranking reflects its own editorial logic — use sort: recent when you want pure chronology. The actor indexes coverage; article-level analysis follows the URLs.
Related use cases
Frequently asked questions
What does the news surface return?
Ranked news records: headline, article URL, publisher (the Korean outlet), relative publish date, and the query that matched — across searchType 'news' or the integrated 'all' view.
Can I restrict to recent coverage?
Yes — period accepts day, week, month, 3months, 6months, year. Pair with sort 'recent' for a pure latest-first feed.
How do I track an industry, not a brand?
Query the industry's Korean terms — sector names, technology keywords, regulation names. The queries list covers as many terms as your beat needs.
Does it include article text?
Records carry headline, URL, outlet, and date. Fetch the article text from the URL for deeper analysis — the export is your index of what's new.