Google Scholar Scraper

Collect ranked Scholar results for research topics. Rows include paper titles, result IDs, publication summaries, snippets, links, and available resources.

What data can you extract?

Field	Type	Description
position	Integer	Position of the paper in Google Scholar results, starting at 1.
title	String	Paper title displayed by Google Scholar.
result_id	String	Google Scholar identifier associated with the paper record.
link	String	Google Scholar or publisher URL for the paper.
snippet	String	Short paper excerpt or matching text shown in Scholar results.
publication_info	Object	Publication venue, authors, and year displayed with the paper.
resources	Array<object>	Publisher and document links associated with the paper.
input_q	String	Research phrase submitted to Google Scholar for this result set.
scraped_at	String	UTC date and time when this paper record was collected.

Use cases

• Researchers can collect paper details and publisher links by topic.
• Librarians can build reading lists from ranked Google Scholar results.
• Research teams can monitor publication coverage for recurring queries.

How to use

1. Add one research phrase per item in queries.
2. Set maxPages to bound collection and maxResults to cap saved papers.
3. Review paper titles, publication details, links, and resources.

{
  "queries": [
    {
      "q": "transformer attention"
    }
  ],
  "maxResults": 20,
  "maxPages": 2
}

Input

Field	Type	Required	Description
queries	Array<object>	Yes	Academic search phrases. Add one object per phrase.
queries[].q	string	Yes per entry	Scholar search query. Optional when cites or cluster is supplied.
queries[].hl	string	No	Two-letter interface language, optionally with a region. Defaults to en.
queries[].start	integer	No	Zero-based result offset from 0 to 990. Defaults to 0.
queries[].num	integer	No	Results per request from 1 to 20. Defaults to 10.
queries[].as_ylo	integer	No	Earliest publication year to include.
queries[].as_yhi	integer	No	Latest publication year to include.
queries[].scisbd	integer	No	0 for relevance, 1 for recent abstracts, or 2 for all recent additions. Allowed values: 0, 1, 2.
queries[].cites	string	No	Numeric publication ID for a cited-by search. May be combined with q.
queries[].cluster	string	No	Numeric publication ID for an all-versions search. Must be used alone.
hl	string	No	Two-letter interface language, optionally with a region. Defaults to en.
start	integer	No	Zero-based result offset from 0 to 990. Defaults to 0.
num	integer	No	Results per request from 1 to 20. Defaults to 10.
as_ylo	integer	No	Earliest publication year to include.
as_yhi	integer	No	Latest publication year to include.
scisbd	integer	No	0 for relevance, 1 for recent abstracts, or 2 for all recent additions. Allowed values: 0, 1, 2.
cites	string	No	Numeric publication ID for a cited-by search. May be combined with q.
cluster	string	No	Numeric publication ID for an all-versions search. Must be used alone.
maxResults	integer	No	Maximum dataset items to save across this entire run.
maxPages	integer	No	Maximum pages to request for each batch entry.

Output example

{
  "position": 1,
  "title": "How Search Interfaces Shape Literature Reviews",
  "result_id": "GS-2025-01842",
  "link": "https://scholar.google.com/scholar?cluster=1748293102842",
  "snippet": "This study compares citation discovery and screening workflows across digital research libraries.",
  "publication_info": {
    "summary": "Journal of Digital Scholarship, 2025",
    "authors": [
      "Priya Menon",
      "Rafael Costa"
    ]
  },
  "resources": [
    {
      "title": "Open access article",
      "file_format": "PDF",
      "link": "https://repository.uni-muenster.de/document/1842"
    }
  ],
  "input_q": "transformer attention",
  "scraped_at": "2026-10-01T12:00:00Z"
}

Pricing

$0.30 per 1,000 results. Apify saves one dataset item per result and applies the Actor’s per-result price to saved items.

Pagination follows the source response. Set maxPages per batch entry and maxResults across the run.

FAQ

Is scraping this information legal?

Rules depend on the source, location, data type, and intended use. Check applicable laws and source terms, and make sure your workflow follows privacy and data protection requirements.

What limits apply?

Submit up to 100 batch entries per run. Use maxResults to cap saved items and maxPages to limit pages for each entry. Results also depend on source availability and your Scrappa API plan.

Can I start runs through the Apify API?

Yes. Send a POST request to https://api.apify.com/v2/acts/thescrappa~google-scholar-scraper/runs with your Actor input, or use an Apify client library. Read the output from the run dataset.

Can I connect the results to other tools?

Yes. Apify integrations and APIs can pass dataset results to Make, Zapier, n8n, Google Sheets, and other data workflows.

What happens when one input fails?

The Actor logs a short source error and continues with the remaining entries. Transient rate limits and gateway errors are retried; if every entry fails, the run reports an error.

Does the Actor download full papers?

No. It returns result metadata and resource links exposed in search results; publisher access rules still apply.

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