Some highlights of VOSviewer are summarized below.
Data
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.
Visualization
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.
Techniques
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.