University of California, Irvine: What does a university look like?
University of California, Irvine
About the Researchers
The network above represents a connected graph of 12,085 co-authored researchers affiliated to the University of California, Irvine from 2017-2022, making up 90% of all affiliated researchers over this time period. Each researcher has been colour coded by the 2-digit FoR 2020 code they are most associated with. Each researcher is depicted by a sphere, and given a size based on the number of publications produced.
About the Clusters
127 research clusters were identified in the network above. To make the network easier to read, collaborations between clusters are not displayed, although they do play a significant role in the layout of the network. Clusters of 20 or more researchers can be explored further in the associated figshare record (linked in the QR code top right). Clusters are colour coded by the most dominant discipline of the researchers within them, and are given a ‘height' based on the discipline that they proportionally belong to. Biomedical and Clinical Sciences clusters sit at the base of the network, with Language, Communication and Culture sitting at the top.
About the Classifications
The 2020 Field of Research codes used in this analysis have been assigned to publications using the approach detailed in “Recategorising research: Mapping from FoR 2008 to FoR 2020 in Dimensions” (https://doi.org/10.1162/qss_a_00244.) Note: some research areas are not well represented in the network due to single author publications. Fields of Research with greater than 50% of their output not represented in the network include: Mathematical Sciences (50.48%), Commerce, Management, Tourism and Services (51.57%), Language, Communication and Culture (54.23%), Law and Legal Studies (58.81%), Human Society (61.04%), Creative Arts and Writing (64.02%), Philosophy and Religious Studies (68.3%), Economics (71.43%), and History, Heritage and Archaeology (82.67%)
Methodology:
Graph layout: Batchlayout [1]
Clustering: Leiden Algorithm [2]
3d Layout: Blender [3]
Data: Dimensions [4]
