Google Scholar Paper and Author Data Scraper

Search Google Scholar and extract structured papers, citation formats, author profiles, publication lists, citation histories, and co-author relationships. The Actor combines a direct Camoufox research path with managed or bring-your-own SerpApi routing and returns provenance with each record.

Use it for literature discovery, bibliometric analysis, researcher enrichment, citation workflows, knowledge graphs, and AI research agents.

Best fit

• Researchers assembling literature-review candidates around a topic.
• Academic teams organizing author profiles and publication portfolios.
• Data analysts studying citation history and co-author networks.
• Reference managers collecting formatted citations and export links.
• AI agents retrieving scholarly evidence for downstream synthesis.

A practical research scenario

A research analyst begins with a Scholar search for transformer architecture and narrows the result set by year. Each paper provides a resultId plus author identifiers where Scholar exposes them. The analyst can route the paper IDs into citation mode and the author IDs into profile, publication, citation-history, or co-author modes. The result is a connected evidence set that moves from topic discovery to reference formatting and researcher context.

This workflow keeps every step explicit and lets an agent choose the smallest mode needed for the current question.

Modes

Mode	Input	Result
search	queries	Papers, authors, venues, years, citation counts, links, and result IDs.
cite	resultIds	Formatted citation strings and bibliographic export links.
author_profile	authorIds	Affiliation, interests, citation totals, h-index, and i10-index.
author_articles	authorIds	Publications associated with each Scholar author.
author_citation	authorIds	Citation totals organized by year.
author_co_authors	authorIds	Co-author names, IDs, and relationship records.

Quick start

Search for papers

{
  "mode": "search",
  "queries": ["transformer architecture"],
  "yearFrom": 2020,
  "maxResults": 20,
  "resultsLanguage": "en"
}

Read an author profile

{
  "mode": "author_profile",
  "authorIds": ["LSsXyncAAAAJ"]
}

Collect citation formats

{
  "mode": "cite",
  "resultIds": ["u-CT435A0vkJ"]
}

Citation mode uses the configured SerpApi route. The Actor includes a managed key, and the optional serpApiKey field is marked secret for teams that prefer their own provider account.

Input reference

Field	Purpose
mode	Selects the Scholar operation.
queries	Search phrases for paper discovery.
resultIds	Scholar paper or cluster IDs for citation export.
authorIds	Scholar author identifiers for author modes.
maxResults	Upper bound for records per target.
yearFrom, yearTo	Narrows paper searches by publication year.
sortByDate	Requests date-oriented paper ordering.
includePatents, includeCaseLaw	Selects additional Scholar document surfaces.
reviewArticlesOnly	Focuses search on review literature.
languageRestrict	Applies a Scholar language restriction.
authorSort	Orders author publications by relevance, date, or title.
resultsLanguage	Selects the interface and returned language context.
forceSerpApi	Routes supported work directly through SerpApi.
serpApiKey	Optional secret-marked bring-your-own provider key.
proxyConfiguration	Controls direct Scholar browsing sessions.

Output data

Paper records can include title, authors, publicationInfo, year, snippet, citedByCount, resultId, article links, PDF links, version counts, provenance, and capture time.

Author modes can add name, authorId, affiliation, interests, profile image, citation totals, h-index, i10-index, year-by-year citation data, publication records, and co-author edges. Citation mode can add formatted citations and export links.

{
  "mode": "search",
  "query": "transformer architecture",
  "position": 1,
  "title": "Attention Is All You Need",
  "resultId": "u-CT435A0vkJ",
  "year": 2017,
  "authors": [
    {
      "name": "A Vaswani",
      "authorId": "author-id"
    }
  ],
  "source": "serpapi"
}

The source field identifies whether a result came from the direct Camoufox path or SerpApi routing.

AI agent workflows

The mode-specific contract supports compact tool calls through Apify MCP and direct API integrations.

Example agent request:

Find papers about retrieval-augmented generation, keep recent publications, return paper IDs and author IDs, then collect citation formats for the selected papers.

Useful routing guidance:

• Start with search when the agent has a topic or research question.
• Use cite when the workflow already has Scholar result IDs.
• Use author_profile for researcher metrics and identity context.
• Use author_articles for publication discovery around a known author.
• Use author_citation and author_co_authors for bibliometric graphs.
• Preserve source and resultId in downstream evidence records.

Run through the API

curl -X POST "https://api.apify.com/v2/acts/khadinakbar~google-scholar-scraper/runs" \
  -H "Authorization: Bearer YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "mode": "search",
    "queries": ["retrieval augmented generation"],
    "maxResults": 20,
    "resultsLanguage": "en"
  }'

The Apify token stays in the Authorization header. Provider credentials supplied through the Console remain in the secret-marked input field.

Data sourcing and recovery

The primary research path uses Camoufox browser sessions with residential routing and parses Scholar paper and author pages directly. When Scholar presents its traffic-verification surface, the Actor can continue the same target through the configured SerpApi route. Citation export uses SerpApi because that workflow maps cleanly to the provider's structured citation endpoint.

Managed and bring-your-own provider results share the same dataset contract, caps, and billing flow. Record provenance remains visible through source.

Pricing

This Actor uses Pay per event pricing with platform usage passed through. Result events cover paper, citation, citation-history, and co-author records, while author profiles have their own event. Treat the live Pricing tab as the current source of truth for event prices and billing details.

Use maxResults, focused queries, and year filters to align each run with the research question.

Best results

• Begin with a focused query and a practical result cap.
• Use year and document filters when the research brief has a defined scope.
• Chain resultId and authorId fields into the corresponding enrichment modes.
• Use direct SerpApi routing for time-sensitive research batches and citation export.
• Retain provenance fields when combining Scholar data with external evidence.

Related Actors

• Use Google Patents Scraper when scholarly research should connect to patents, assignees, inventors, and patent citations.
• Use Google SERP Scraper when the research brief expands from academic literature to the broader web.

Builder's note

I designed the six modes as a connected research path rather than unrelated endpoints. Search records expose the IDs needed by citation and author workflows, while the source field keeps direct and provider-backed evidence easy to audit in a combined dataset.

Responsible use

This Actor collects publicly available scholarly metadata. Use the results for legitimate research, indexing, and analysis in line with applicable laws, source terms, citation practices, and your organization's data-governance requirements.