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The Naver Academic scraper turns article detail pages from Naver Academic into a structured CSV for literature review, Korean research monitoring, and bibliographic cleanup. Import the workflow, replace the sample article URLs with your own collected doc_id pages, and export titles, authors, affiliations, journal details, DOI, citations, subject areas, keywords, and access signals without writing scraper code.
CSV
21
URL list
Naver Academic
Free import
At a glance
Naver Academic is useful when Korean research teams need paper-level metadata, but copying each record by hand quickly becomes repetitive. This template is built for detail-page extraction: you collect the article URLs for your approved keyword search, paste or extend them inside the Navigate block, and let UScraper visit each page in sequence.
The automation is intentionally easy to audit. It follows a Navigate -> wait for page load -> wait for .wrap -> short sleep -> Structured Export -> Loop Continue flow. That means the page gets time to render before the export block reads the visible record and writes a row. Use it when you need to scrape Naver Academic, compare papers across topics, or move Naver Academic to CSV for review in Excel, Sheets, Zotero prep sheets, or internal research databases.
Capture article-level metadata
Extract research fields that analysts usually need for screening: title, author, affiliation, journal, publication year, DOI, citation count, provider, subject area, and keyword text.
Run a controlled URL list
The bundled project starts with four sample article URLs. Replace or extend that list with detail pages collected from your own Naver Academic search.
Append clean CSV rows
Structured Export writes headers and appends each article record into the same file, so repeated runs can build one review spreadsheet.
Keep research custody local
The browser session and CSV output stay on your computer. Nothing in the stock template sends exported rows to UScraper servers.
Who uses it
Academic researchers
Literature screening
Build a first-pass corpus from Naver Academic article pages, then filter by year, journal, subject area, provider, DOI availability, and citation count before deciding which papers to read.
Research assistants
Metadata cleanup
Replace manual copying with a repeatable CSV export when faculty or analysts ask for paper titles, author names, affiliations, ISSNs, publishers, and Korean keyword fields.
Market and policy teams
Evidence gathering
Track academic attention around technology, labor, education, health, or regulatory topics without rebuilding the same Naver Academic spreadsheet every week.
How to use
Download and import
Download the hosted template JSON from the Naver Academic Scraper template link, then import it into UScraper.
Replace the article URLs
Open the Navigate block and replace the sample academic.naver.com/article.naver?doc_id=... URLs with the article detail pages you collected for your keyword search.
Confirm the export path
Check the Structured Export save location and keep append mode if you want every URL in one CSV.
Run the workflow
UScraper visits each URL, waits for the page wrapper, pauses briefly, then extracts the configured article metadata columns.
Open and verify the CSV
Review naver-academic-scraper.csv, spot-check a few rows against the source pages, and rerun with smaller batches if Naver shows verification or slow responses.
Output preview
naver-academic-scraper.csvColumn
title
Article title from page metadata or document title.
Column
author
Author names when shown on the detail page.
Column
affiliation
Institutional affiliation text parsed from the page body.
Column
journal_info
Journal, conference, or publication container details.
Column
doi
DOI string when Naver exposes one.
Column
citation_count
Citation count displayed by Naver Academic.
Sample rows
2 of many
| title | author | affiliation | journal_info | doi | citation_count |
|---|---|---|---|---|---|
| Effects of AI education programs on learner engagement | Kim H.; Park J. | Korea National University | Journal of Digital Learning 18(2) | 10.0000/example.2024.18.2 | 17 |
| Semiconductor regulation and supply-chain strategy | Lee S. | Policy Research Institute | Korean Policy Review 31(1) | 5 |
| CSV column group | Fields included |
|---|---|
| Page identity | title_link, doc_id, search_keyword, data_type |
| Publication metadata | title, subtitle, author, affiliation, journal_info, issn, publisher, publication_info, publish_year |
| Research signals | citation_count, data_provider, doi, subject_area, keywords |
| Access signals | price, original_view_count, library_link_count |
Use this template alongside the RISS Academic Information Search Scraper when you need a Korean academic database comparison. For wider discovery, pair it with the Naver Search Scraper, Google SERP Scraper, or the full UScraper template library. Install the local desktop app from uscraper.io/download before importing the JSON.
Naver Academic pages can contain publicly visible metadata, but automated collection may still be limited by Naver terms, robots directives, copyright in abstracts, database rights, privacy rules, institutional access terms, or local law. Keep volume modest, do not bypass CAPTCHA or login controls, and get legal review before publishing, reselling, or training models on exported records.
Before you run
Guardrails for reliable Naver Academic exports
Avoid aggressive batches
Naver may present CAPTCHA, slow responses, or rate limits when browsing looks automated. Keep the waits, avoid parallel runs, and stop when the site asks for human verification.
Watch for selector drift
The Structured Export block reads visible Korean labels and page text. If Naver changes article detail layouts, empty fields are the signal to inspect the page and refresh the export columns.
Treat metadata as governed research data
Article metadata, abstracts, and provider links can carry platform, publisher, or institutional terms. Keep datasets purpose-limited and review rules before redistribution or commercial reuse.
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