Familiarity with R. Previous experience with the
statnet packages (
networkDynamic) is helpful but not required.
This workshop provides an introduction to exploring temporal network data in
statnet, using the R packages
tsna. The software can be used for both empirical networks and simulated network data. The topics covered include:
- how to import, transform and extract relational data with timing information from various data structures (matrices, spell lists, toggles, etc)
- advantages of various temporal models and representations (continuous vs discrete time, etc)
- slicing and aggregating time in temporal networks
- calculating temporal network statistics using the tsna package, including temporal paths and basic sequence measures
- visualizing temporal networks using non-animation techniques such as relationship timelines, filmstrips and other projections
- visualizing network dynamics using animation (network movies), including exporting network animations as videos or interactive HTML5 web pages.
- attaching and manipulating dynamic vertex and edge attributes and effectively using a range of graphical properties to represent them (color, shape, size, transparency, speed, and annotation).
- common visualization challenges, such as adjustments needed when working with networks with disconnected components
- how to determine if a network has appropriate size and density to create an animation.