Google Scholar Research Scraper searches public scholarly results with a configurable keyword and returns structured research records, including citation and document links when visible.
What Does BrowserAct Google Scholar Research Scraper Do?
This BrowserAct template runs a validated, reusable extraction path against publicly accessible pages. Configure the inputs, run the Bot, and receive structured records without writing selectors or browser scripts.
Key Features
- Construct a Google Scholar query from a reusable keyword.
- Read public scholarly result cards.
- Paginate when more results are required and available.
- Capture citation, PDF, DOI, and related-article links when visible.
- Keep optional fields empty instead of inferring unavailable values.
What Data Can I Extract from Google Scholar?
Field | Description |
|---|---|
| Research work title. |
| Visible author list. |
| Visible publication year. |
| Publication venue or source. |
| Visible cited-by count. |
| Result snippet or abstract when visible. |
| Direct PDF link when exposed. |
| Primary result URL. |
| DOI when visible. |
| Google Scholar related-articles URL when available. |
How to Use Google Scholar Research Scraper
- Click Run task.
- Enter the configurable values shown below.
- Run the Bot and review the structured records.
- Export the result or connect it to an API, automation platform, or agent workflow.
Input Parameters
Parameter | Required | Default | Description |
|---|---|---|---|
| Yes |
| Research query sent to Google Scholar. |
| Yes |
| Maximum scholarly records to return. |
Example Output
One actual record from a completed validation run is shown below.
| Field | Result |
|---|---|
title |
A survey of webagents: Towards next-generation AI agents for web automation with large foundation models |
authors |
L Ning, Z Liang, Z Jiang, H Qu, Y Ding, W Fan |
publication_year |
2025 |
venue |
Proceedings of the 31st |
citation_count |
148 |
abstract |
A survey of web agents and browser-navigation agents powered by large foundation models. |
pdf_url |
https://dl.acm.org/doi/pdf/10.1145/3711896.3736555 |
result_url |
https://dl.acm.org/doi/abs/10.1145/3711896.3736555 |
doi |
10.1145/3711896.3736555 |
related_articles_url |
https://scholar.google.com/scholar?q=related:FmeGRrsSS6QJ:scholar.google.com/ |
How Does it Work?
BrowserAct constructs the public Google Scholar search URL from Keyword, opens the results page, and reads the visible scholarly result cards.
The Bot captures the requested research fields, preserves optional links only when visible, and paginates until Count is reached or no more results are available. The successful default run returned ten records.
How to Build a New Scraper Bot with Agent Built
Step 1: Describe the Data You Need
Open BrowserAct and start Agent Built from the Home prompt box or from Create -> Build with Agent. Paste a clear request that includes the website, the records to collect, the filters or search conditions, the fields to return, the result limit, and the inputs you want to reuse later.
Step 2: Let BrowserAct Build and Test the Bot
BrowserAct explores the live website, works out the navigation and extraction path, and validates the result. If BrowserAct asks for clarification, reply in the same build conversation with the missing URL, condition, field, example, or expected output.
Step 3: Run the Bot and Review the Result
When the build is complete, run the Bot with the default inputs first. Review the structured records, source URLs, missing fields, and row count before reusing the Bot with new inputs or connecting it to another workflow.
Why Use Google Scholar Research Scraper?
Build structured literature lists for research discovery, citation review, topic monitoring, and academic source enrichment.
Who Can Use This Template?
- Academic and market researchers.
- R&D and competitive-intelligence teams.
- Students organizing public sources.
- Automation builders preparing literature datasets.
How Many Results Can You Scrape?
Count controls the maximum records. Keep runs moderate because Google Scholar may apply public traffic limits or verification checks.
Automation and Export
BrowserAct returns structured data first. You can then use the completed output through API JSON responses, n8n workflows, Make scenarios, Zapier automations, MCP-based agent workflows, or manual CSV and spreadsheet review.
Need Help?
Contact us at
Discord: Discord Community
E-mail: service@browseract.com
