seismic: Predict Information Cascade by Self-Exciting Point Process

An implementation of self-exciting point process model for information cascades, which occurs when many people engage in the same acts after observing the actions of others (e.g. post resharings on Facebook or Twitter). It provides functions to estimate the infectiousness of an information cascade and predict its popularity given the observed history. See http://snap.stanford.edu/seismic/ for more information and datasets.

Author
Hera He, Murat Erdogdu, Qingyuan Zhao
Date of publication
2015-06-05 22:23:38
Maintainer
Qingyuan Zhao <qingyzhao@gmail.com>
License
GPL-3
Version
1.0
URLs

View on CRAN

Man pages

get.infectiousness
Estimate the infectiousness of an information cascade
linear.kernel
Integration with respect to locally weighted kernel
memory.pdf
Memory kernel
pred.cascade
Predict the popularity of information cascade
seismic
Predicting information cascade by self-exciting point process...
tweet
An example information cascade

Files in this package

seismic
seismic/NAMESPACE
seismic/data
seismic/data/tweet.rda
seismic/R
seismic/R/tweetfunctions.R
seismic/MD5
seismic/DESCRIPTION
seismic/man
seismic/man/pred.cascade.Rd
seismic/man/get.infectiousness.Rd
seismic/man/seismic.Rd
seismic/man/tweet.Rd
seismic/man/memory.pdf.Rd
seismic/man/linear.kernel.Rd