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NetworkInference (version 1.2.5)

Inferring Latent Diffusion Networks

Description

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.

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Install

install.packages('NetworkInference')

Monthly Downloads

220

Version

1.2.5

License

MIT + file LICENSE

Maintainer

Fridolin Linder

Last Published

November 28th, 2025

Functions in NetworkInference (1.2.5)

sim_validation

Larger simulated validation network.
simulate_cascades

Simulate cascades from a diffusion network
subset_cascade

Select a subset of cascades from cascade object
simulate_rnd_cascades

Simulate a set of random cascades
validation

Validation output from netinf source.
plot.cascade

Plot a cascade object
as_cascade_wide

Transform wide data to cascade
cascades

Example cascades
as.matrix.cascade

Convert a cascade object to a matrix
count_possible_edges

Count the number of possible edges in the dataset
drop_nodes

Drop nodes from a cascade object
NetworkInference

NetworkInference: Inferring latent diffusion networks
as_cascade_long

Transform long data to cascade
is.diffnet

Is the object of class diffnet?
as.data.frame.cascade

Convert a cascade object to a data frame
is.cascade

Is the object of class cascade?
subset_cascade_time

Subset a cascade object in time
plot.diffnet

Visualize netinf output
summary.cascade

Summarize a cascade object
netinf

Infer latent diffusion network
policies

US State Policy Adoption (SPID)