Academic Research & Citation Mapper

Map research landscapes for any scientific topic using the OpenAlex API, which indexes over 240 million academic works across all disciplines. This actor retrieves structured data about papers, authors, institutions, citation counts, journal sources, and open access availability, making it easy to analyze trends and build comprehensive bibliometric datasets.

What data does it extract?

For each paper matching your search query, the actor returns:

• Title and DOI for precise identification
• Authors with full name lists
• Institutions affiliated with each author
• Journal or source where the paper was published
• Publication year and date
• Citation count (cited-by count from OpenAlex)
• Open access status indicating whether the paper is freely available
• Top concepts (up to 5 research topics tagged by OpenAlex with relevance scores)
• Direct URL to the paper (DOI link when available, otherwise OpenAlex link)

Use cases

Pharma R&D landscape analysis

Map the research landscape around a drug target, therapeutic area, or mechanism of action. Identify which institutions and research groups are publishing the most, track citation momentum to spot emerging breakthroughs, and filter for open access papers to streamline literature reviews during drug discovery.

University technology transfer

Technology transfer offices can use this actor to monitor publications from their own institution or competitors, identify highly cited works that may indicate patentable discoveries, and track collaboration patterns between universities and industry labs.

VC deep-tech scouting

Venture capital firms investing in deep technology can scan research areas like quantum computing, synthetic biology, or advanced materials to find the most active research groups, track citation velocity as a proxy for impact, and identify potential founders or advisors in emerging fields.

Bibliometric analysis and meta-research

Researchers studying the research process itself can build datasets for bibliometric analysis. Measure publication volumes over time, analyze open access adoption rates across disciplines, compare citation distributions between journals, and identify influential works in any field.

Competitive intelligence for research organizations

Track what competitors are publishing, in which journals, and how their work is being cited. Build dashboards showing publication trends by institution, author, or topic to inform strategic research planning.

Input parameters

Parameter	Type	Description
query	string	Research topic, keyword, or phrase to search for (required)
fromYear	integer	Filter papers published from this year onwards
toYear	integer	Filter papers published up to this year
openAccessOnly	boolean	Only return open access papers (default: false)
maxResults	integer	Maximum number of results to return (default: 100, max: 2000)

API and rate limits

This actor uses the OpenAlex API with the polite pool (identified via mailto parameter), which provides generous rate limits for automated access. No API key is required. Results are paginated automatically until the requested number of papers is collected or no more results are available.

Example input

{
  "query": "machine learning",
  "maxResults": 50
}

Example output

{
  "source": "OpenAlex",
  "openAlexId": "W2100837269",
  "doi": "https://doi.org/10.1038/nature14539",
  "paperTitle": "Deep learning",
  "authors": ["Yann LeCun", "Yoshua Bengio", "Geoffrey Hinton"],
  "institutions": ["Facebook AI Research", "Universite de Montreal", "University of Toronto"],
  "journal": "Nature",
  "publicationYear": 2015,
  "publicationDate": "2015-05-28",
  "citedByCount": 42350,
  "isOpenAccess": false,
  "topConcepts": ["Deep learning", "Artificial intelligence", "Convolutional neural network", "Recurrent neural network", "Feature learning"],
  "url": "https://doi.org/10.1038/nature14539",
  "scrapedAt": "2025-01-15T10:30:00.000Z"
}

Pricing

• $0.35 per actor start
• $0.02 per result record