Sigma Co-Authorship Network
Academic co-authorship network of 60 researchers across four lab groups, where node size encodes the researcher's total paper output and edge thickness encodes how many papers two authors have co-written. ForceAtlas2 reveals that co-authorship dramatically clusters by lab — withi
Template details
- chart
- network
- graph
- sigma
- sigmajs
- webgl
- coauthorship
- academic
- bibliometrics
When to use this template
This visualization excels at revealing the structure of relationships within a network, making it easy to identify dense communities, influential central figures, and critical bridging connections. An analyst would reach for it to understand collaboration patterns, resource flow, or communication pathways, especially when seeking to surface key actors and group dynamics.
- Relational data with distinct entities and connections.
- Edges representing quantifiable interactions between entities.
- Nodes with a measurable attribute for size encoding.
- Nodes possessing a categorical attribute for color coding.
- Networks where identifying clusters or communities is key.
- Datasets where 'who interacts with whom and how much' is core.