Academic researchers
Literature discovery
Favorable to scraping
Collect a reviewable shortlist for a seed topic, then screen titles, snippets, years, and citation counts before moving papers into a manual reading queue.
Search Engine$50Free
Google Scholar Scraper for CSV Export
This Google Scholar scraper turns a Scholar keyword search into a structured CSV for literature scans, topic monitoring, and research operations. Import the template into the UScraper local desktop app, run the bundled navigate-wait-loop workflow, and export titles, authors, publication years, snippets, citation counts, version counts, article links, and related-article links without building a crawler or wiring a Google Scholar API.
Output
CSV
Columns
8
Pagination
Next loop
Waits
Built in
Template
Free
At a glance
Export Google Scholar results into a local CSV
The workflow starts at a Google Scholar search URL for the sample query data mining. UScraper sets a full-size browser viewport, navigates to Scholar, waits for the page to finish loading, pauses briefly, and then checks whether result cards exist. When they do, Structured Export writes one row per result card.
After each export, the graph looks for the next-page control and clicks it when available. That loop continues until Scholar stops offering another page. If the first Scholar check fails because of a CAPTCHA, 403 page, or no-result state, the workflow moves to an accessible IEEE article detail page and exports the same column family where possible.
Research metadata in spreadsheet form
Export article title, visible author text, detected year, snippet, outbound article URL, cited-by count, all-versions count, and related-articles URL for review in Excel, Sheets, or a research database.
Click-next pagination
The template does not require you to prebuild every offset URL. It follows Scholar pagination while the next control remains visible, then ends cleanly.
Local desktop app custody
The browser session runs on your machine and the CSV lands in the folder configured in Structured Export. Raw research files stay under your control.
Fallback branch for blocked runs
Scholar can challenge automated traffic. The IEEE fallback keeps the output schema testable so teams can verify downstream CSV handling even when Scholar throttles the first path.
Who this is for
Teams that need Google Scholar data extracts
Market intelligence teams
Research monitoring
Favorable to scraping
Track technology phrases, company names, or methods across visible Scholar results and keep a timestamped CSV for internal analysis.
Data operations teams
Workflow prototyping
Favorable to scraping
Use the block graph as a no-code starting point for approved, low-volume Google Scholar extractor work before deciding whether a paid API or custom crawler is justified.
How to use
Run the Google Scholar scraper
1
Download and import
Download the hosted JSON template from this page, import it into UScraper, and open the graph before running the first batch.
2
Set the Scholar query
Replace the sample data mining search URL with your approved Google Scholar keyword. Keep the first test narrow so you can inspect behavior before scaling.
3
Review the export path
Structured Export writes google-scholar-scraper.csv with headers and append mode enabled. Change the save folder if your team stores research files in a shared location.
4
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.
5
Open the output
Review row counts, spot-check article links, and preserve blank Scholar-only fields when the IEEE fallback branch runs.
Automation path inside the template
- 1
Navigate
Open the configured Google Scholar keyword search in a desktop browser session.
- 2
Wait, inspect, and branch
Wait for load, pause for rendering, then check whether Scholar result cards are present.
- 3
Structured export
Append article metadata from each Scholar row, or export the IEEE fallback article when Scholar blocks the path.
- 4
Loop or end
Click the next-page control while it exists; otherwise terminate the workflow.
Output preview
CSV columns produced by the template
The export mirrors the visible Scholar result card. It is designed for fast screening, not full bibliographic normalization, so author strings and snippets should be reviewed before citation management or publication use.
| title | author | published_year | description | article_link | cited_for | all_versions | related_articles_link |
|---|---|---|---|---|---|---|---|
| Data mining: concepts and techniques | J Han, M Kamber, J Pei | 2012 | This book introduces major data mining methods, pattern discovery, and applications. | https://example.edu/data-mining-book | 45231 | 18 | https://scholar.google.com/scholar?q=related:example |
| A survey of data mining methods for big data | A Researcher, B Analyst | 2021 | Survey paper covering scalable classification, clustering, and text mining techniques. | https://example.org/big-data-mining | 842 | 7 | https://scholar.google.com/scholar?q=related:sample |
| Mining association rules between sets of items in large databases | R Agrawal, T Imielinski, A Swami | 1993 | Classic database research article extracted from the IEEE fallback branch. | https://ieeexplore.ieee.org/abstract/document/553155/ |
google-scholar-scraper.csvColumn
title
Scholar result headline or IEEE article title.
Column
author
Visible author segment parsed from the result metadata line or article page.
Column
published_year
First detected 19xx or 20xx publication year.
Column
description
Scholar snippet or article abstract description when available.
Column
article_link
Outbound article URL, or the fallback IEEE article URL.
Column
cited_for
Numeric Cited by count when Scholar or the fallback page exposes it.
Column
all_versions
Scholar all-versions count; blank on the IEEE fallback branch.
Column
related_articles_link
Scholar related-articles link; blank when unavailable.
Sample rows
2 of many
| title | author | published_year | description | article_link | cited_for | all_versions | related_articles_link |
|---|---|---|---|---|---|---|---|
| Data mining: concepts and techniques | J Han, M Kamber, J Pei | 2012 | This book introduces major data mining methods, pattern discovery, and applications. | 45231 | 18 | ||
| Mining association rules between sets of items in large databases | R Agrawal; T Imielinski; A Swami | 1993 | Classic database research article extracted from the IEEE fallback branch. |
Headers included - Scholar pages and the IEEE fallback share the same eight-column shape
Related workflows
Compare and extend your research exports
Use this page when you want a click-next scrape Google Scholar flow. If you prefer generated URL batches, use the Google Scholar batch URL scraper. For broader search coverage, pair it with the Google Search Scraper, the Google SERP Scraper, and the Bing Search Results Scraper. Browse the full UScraper template library when collected article links need deeper extraction.
Frequently asked questions
Automating Google Scholar can implicate Google Terms of Service, robots guidance, publisher rights, privacy rules, and local law even when results are publicly visible. Keep volume modest, do not bypass CAPTCHAs or access controls, and get legal review before commercial reuse.
Before you run
Practical limits to plan around
Guardrails for reliable Google Scholar exports
Rate limits
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.
Layout drift
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.
Compliance
Publisher and platform rules still apply
Review Google policies, Scholar help, publisher terms, and internal acceptable-use rules 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 the workflow whenever you need to export Google Scholar results into a reviewable local CSV.
Get Started
Download and use this template instantly
$50Free
What's Included
- Template JSON file ready to import
- Pre-configured scraping nodes
- Works with UScraper desktop app
Open-source templates
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