Some highlights of VOSviewer are summarized below.
Web of Science, Scopus, Dimensions, Lens, and PubMed. Co-authorship networks, citation-based networks, and co-occurrence networks can be created based on data downloaded from Web of Science, Scopus, Dimensions, and Lens. Co-authorship networks and co-occurrence networks can also be created based on PubMed data.
Crossref, Europe PMC, and OpenAlex. Networks can also be created based on data retrieved through the APIs of Crossref, Europe PMC, and OpenAlex. These APIs can be queried interactively in VOSviewer.
Semantic Scholar, OpenCitations, and WikiData. For a given set of DOIs, networks can also be created based on data retrieved through the APIs of Semantic Scholar, OpenCitations, and WikiData.
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Zooming and scrolling. Visualizations of bibliometric networks can be explored in full detail using zoom and scroll functionality similar to for instance Google Maps. A smart labeling algorithm prevents labels from overlapping each other.
Density and overlay visualizations. Density visualizations provide a quick overview of the main areas in a bibliometric network. Overlay visualizations can for instance be used to show developments over time.
Screenshots. Screenshots of bibliometric network visualizations can be created at a high resolution and can be saved in many popular graphical file formats, both bitmap and vector formats.
Advanced layout and clustering techniques. State-of-the-art techniques for network layout and network clustering are provided. Layout and clustering results can be fine-tuned using various parameters.
Natural language processing techniques. Natural language processing techniques are available for creating term co-occurrence networks based on English-language textual data. Relevant and non-relevant terms can be distinguished algorithmically.
Creating bibliometric networks. A number of advanced features are available for creating bibliometric networks (e.g., co-authorship, bibliographic coupling, and co-citation networks). For instance, the influence of publications with many authors, many citations, or many references can be reduced using a fractional counting approach. Data cleaning can be performed using thesaurus files.