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statnetWeb is a graphical user interface for the statnet suite of R packages!
Using the Shiny framework from RStudio, we have built an application that runs in a web browser and gives the user access to powerful network visualization, analysis and modeling from the ergm, network and sna packages, without requiring software installation or knowledge of programming in R. The typical network analysis workflow is represented by a series of tabs along the top of the screen, with additional options in tabs within each page. Much of the functionality from the packages is available via drop-down menus, and there are context-specific help buttons.
This GUI-based access to statnet is useful for teachers and students of introductory network analysis, for newcomers to exponential random graph models, and for experienced network modelers who want quick, easy access to plots, tables and analysis results for small datasets (< 2000 nodes).
With statnetWeb you can:
- Load and edit network data from R, Excel or Pajek
- Look at plots and summaries of descriptive statistics
- Compare the observed network with null models
- Fit ERGMs to the observed network
- Compare results from different models
- Diagnose the model convergence
- Assess goodness-of-fit
- Simulate networks from the fitted models
- Customize and download plots and summaries for later use
There are two ways to interact with the application (links are on the sidebar on the right).
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Online, via the shinyapps.io server. This requires no local software installation, the app runs entirely in a browser window.
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Locally from the R command line. This requires local installation of R, statnetWeb and the packages it depends on.
We maintain a set of online tutorials from our workshops for all of the statnet packages on our website statnet.org. If you're new to network analysis, and to ERGMs, these tutorials can help get you started.
statnetWeb is under active development, so stay tuned for updates and let us know if you encounter issues.
If you have questions about how to use statnetWeb or interpret output, please share them with us via the statnet_help mailing list
Please report bugs, suggestions or complaints about statnetWeb on the GitHub repository