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This Google Scholar Japan scraper turns a Japanese Scholar keyword search into a structured CSV for literature scans, academic monitoring, and research operations. Import the template into the UScraper local desktop app, run the navigate-wait-loop workflow, and export article titles, authors or source text, summaries, article URLs, cited-by counts, version counts, and related-articles URLs without building a crawler or wiring a Google Scholar API.
CSV
7
Next loop
Built in
Free
At a glance
The workflow starts at scholar.google.co.jp with the sample keyword スクレイピング. UScraper navigates to the search page, waits for the browser to finish loading, pauses for rendering, and checks whether Scholar result cards are present. When rows exist, Structured Export writes one CSV row per article result.
After each export, the graph looks for a Japanese or English next-page control. If it finds one, the template clicks it, waits again, and loops back into the same export block. If Scholar returns a CAPTCHA, 403 page, or empty result state before rows appear, the false branch opens an IPSJ article URL and exports equivalent article metadata with citation-related fields left blank where the page does not expose them.
Research metadata in one file
Export title, authors or source line, summary, article URL, cited-by count, versions count, and related-articles URL for review in Excel, Sheets, Airtable, or a research database.
Pagination without URL batches
The template follows Scholar's Next link while it remains available, which is useful when you want to scrape Google Scholar from one approved query instead of building offset URLs.
Local desktop app custody
The browser session runs on your machine and the CSV lands in the folder configured in Structured Export. Your raw research export stays under your control.
Fallback for blocked runs
Google Scholar can challenge automated traffic. The IPSJ fallback keeps the output shape visible so teams can test downstream CSV handling even when Scholar throttles the first path.
Who this is for
Academic researchers
Literature discovery
Collect a reviewable shortlist for Japanese-language research topics, then screen titles, abstracts, citation signals, and article links before moving papers into a manual reading queue.
R&D and market intelligence teams
Topic monitoring
Track methods, technologies, or company names across visible Scholar results and keep a timestamped CSV that analysts can filter by citation count, source text, or related-article link.
Data operations teams
Workflow prototyping
Use the graph as a no-code Google Scholar extractor before deciding whether a paid API, licensed dataset, or custom research crawler is justified.
How to use
Download and import
Download the hosted JSON template from this page, import it into UScraper, and open the workflow before the first run.
Set the Scholar keyword
Replace the sample スクレイピング search URL with your approved Google Scholar Japan query. Keep the first test narrow so you can inspect behavior before scaling.
Review the export path
Structured Export writes google-scholar-jp-article-scraper.csv with headers and append mode enabled. Change the save folder if your team stores research files elsewhere.
Run the browser flow
UScraper navigates, waits, checks for result rows, exports article data, looks for the next button, clicks it, waits again, and loops.
Open the output
Review row counts, spot-check article URLs, and preserve blank citation fields when the IPSJ fallback branch runs.
Automation path inside the template
Navigate
Open the configured Google Scholar Japan keyword search in a local browser session.
Wait and branch
Wait for page load, pause for rendering, then check for Scholar result rows.
Structured export
Append article metadata from each Scholar row, or export the IPSJ fallback article when Scholar blocks the path.
Loop or end
Click the next-page control while it exists; otherwise terminate the workflow.
Output preview
The export mirrors the visible Scholar result card rather than trying to normalize full bibliographic records from downstream publisher pages. That keeps the run easy to audit against the page that was opened.
| title | authors | summary | article_url | cited_by_count | versions_count | related_articles_url |
|---|---|---|---|---|---|---|
| Web scraping for academic data collection in Japan | A Sato, M Tanaka - Journal of Web Research, 2024 | Study discusses automated collection patterns, review workflows, and citation analysis. | https://example.ac.jp/article/web-scraping-japan | 18 | 3 | https://scholar.google.co.jp/scholar?q=related:sample |
| Search result extraction methods for digital libraries | K Yamamoto - Information Processing Review, 2022 | Paper compares metadata extraction from academic search interfaces and repository pages. | https://example.org/digital-library-extraction | 42 | 6 | https://scholar.google.co.jp/scholar?q=related:library |
| IPSJ sample article metadata record | Creator name from IPSJ record | Fallback article summary from the accessible repository page when Scholar rows are blocked. | https://ipsj.ixsq.nii.ac.jp/records/61980 | 1 |
google-scholar-jp-article-scraper.csvColumn
title
Scholar headline or IPSJ article title.
Column
authors
Visible author/source text from the result row or repository metadata.
Column
summary
Scholar snippet or article abstract text when available.
Column
article_url
Outbound article link, PDF link, or fallback repository URL.
Column
cited_by_count
Numeric Cited by count when Scholar exposes it.
Column
versions_count
Numeric versions count when available.
Column
related_articles_url
Scholar related-articles URL when available.
Related workflows
Use this page when the job is Japan-specific export Google Scholar articles work. For a broader Scholar query workflow, use the Google Scholar Scraper. For fixed pagination batches, compare the Google Scholar Batch URL Scraper. To research the same topic outside Scholar, pair it with the Google Search Scraper, the Google SERP Scraper, or the full UScraper template library.
Automating Google Scholar can involve Google Terms of Service, robots guidance, publisher rights, privacy rules, and local law even when result pages are publicly visible. Use modest volumes, do not bypass CAPTCHAs or access controls, and get legal review before commercial reuse.
Before you run
Guardrails for reliable Google Scholar exports
Scholar may throttle or challenge repeated requests
Run small batches, avoid parallel automation, and treat CAPTCHA or 403 pages as a stop condition rather than something to bypass.
Result-card markup can change without notice
Missing titles, empty citation counts, or blank related-article links usually mean the Scholar selectors need review before the next run.
Publisher and platform rules still apply
Review Google Scholar guidance, publisher terms, repository rules, and internal acceptable-use policies before republishing, reselling, or training on exported rows.
Download the JSON template from this page, install the desktop app from uscraper.io/download, and use this workflow whenever you need to download Google Scholar results from the Japan endpoint into a reviewable local CSV.
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