Inferring Latent Diffusion Networks

This is an R implementation of the netinf algorithm (Gomez Rodriguez, Leskovec, and Krause, 2010). Given a set of events that spread between a set of nodes the algorithm infers the most likely stable diffusion network that is underlying the diffusion process.



Current development version

New Features

  • as.cascade is now completely removed (see release note on version 1.1.0).
  • The node_names argument for as_cascade_long and as_cascade_wide will be phased out since it is not doing much. It is still available but not recommended anymore.
  • New convenience function to subset cascades by time (subset_cascade_time) and by cascade id (subset_cascade).
  • We made changes to the internal data structures of the netinf function, so it is much faster and memory efficient now.
  • netinf() now has a shiny progress bar!

Bug Fixes

  • Long running functions (that call compiled code) can now be interrupted without crashing the R session.
  • as_cascade_long() and as_cascade_wide() handle date input correctly now.
  • as_cascade_wide() couldn't handle data input of class data.table.

NetworkInference 1.1.1

Bug Fixes

  • Use of igraph now conditional compliant with Writing R Extensions
  • Fixed version number displayed in startup message

NetworkInference 1.1.0

New Features

  • Data format (long or wide) of as.cascade is not bound to the class of the data object anymore. In 1.0.0 wide format had to be a matrix and long format had to be a dataframe. This did not make much sense. as.cascade is now deprecated and replaced by two new functions as_cascade_long and as_cascade_wide.

Bug Fixes

  • x and y axis labels in plot.cascade with option label_nodes=FALSE were reversed

NetworkInference 1.0.0

First release

Reference manual

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1.2.1 by Fridolin Linder, 13 days ago

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Browse source code at

Authors: Fridolin Linder [aut, cre], Bruce Desmarais [ctb]

Documentation:   PDF Manual  

MIT + file LICENSE license

Imports Rcpp, assertthat, checkmate, ggplot2, ggrepel, stats

Suggests testthat, knitr, rmarkdown, pander, igraph, utils, dplyr

Linking to Rcpp, RcppProgress

System requirements: C++11

See at CRAN