Analyzing OpenAlex Data with VOSviewer || OpenAlex MetaData with VOSviewer || Bibliometric Analysis

OpenAlex can serve as a free, open research metadata source for bibliometric work—especially when paired with VOSviewer to map how scientific papers connect through authors, citations, and bibliographic coupling. The workflow described centers on pulling OpenAlex records via an API, converting the retrieved metadata into a format VOSviewer can analyze, and then generating network visualizations such as author collaboration maps and bibliographic coupling overlays. The practical payoff is clear: researchers can run literature reviews, keyword- or field-based analyses, and comparative checks against other databases without paying for access to proprietary datasets.

The process begins in VOSviewer by choosing a “create” option for a map based on bibliographic data. Instead of manually downloading datasets, the workflow uses “download data through API,” selecting OpenAlex as the API source. Users can tailor the query with fields such as title, abstract, and full text (the transcript keeps full text enabled), apply a search term (example shown: “ECG signal”), and refine results by handling typos and narrowing classification. After the API call, the system retrieves a set of documents (the example run returns 770 documents) along with metadata including author information, venue details (source, volume, issue, page), and references.

Once the dataset is loaded, the analysis step focuses on building networks. For an author network, the workflow sets parameters like the minimum number of documents per author (the transcript shows a threshold in the hundreds) and then runs the “co-authorship” analysis to produce a map where nodes represent authors and links represent relationships. For bibliographic coupling, the workflow switches to a coupling mode (the transcript mentions bibliographic coupling and also references “cited”/“site” style coupling options), using the loaded documents to compute which papers share reference lists. The resulting visualization includes connection density and an overlay view, letting users interpret clusters—such as how research themes cluster around machine learning, data mining, and computer science when the query targets a specific domain.

The transcript also emphasizes usability features that make the outputs easier to reuse: VOSviewer supports exporting or saving visualizations, taking screenshots, and sharing results. The author network and coupling maps can be used to guide literature review structure—identifying key contributors, research communities, and how topics interlink.

A key motivation is validation and comparison. For teams already using Scopus or Web of Science, OpenAlex offers a free alternative to cross-check findings, counterbalance database coverage differences, and run comparative bibliometric analyses. The transcript frames OpenAlex as especially helpful when Web of Science or Scopus access requires subscriptions, while OpenAlex and related components (like Dimension) are presented as free options. Overall, the described pipeline turns OpenAlex metadata into actionable bibliometric maps through VOSviewer, enabling faster, lower-cost literature review analytics and database comparison.