seismic: Predict Information Cascade by Self-Exciting Point Process
Version 1.0

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.

Browse man pages Browse package API and functions Browse package files

AuthorHera He, Murat Erdogdu, Qingyuan Zhao
Date of publication2015-06-05 22:23:38
MaintainerQingyuan Zhao <qingyzhao@gmail.com>
LicenseGPL-3
Version1.0
URL http://snap.stanford.edu/seismic/
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("seismic")

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

Functions

get.infectiousness Man page Source code
integral.memory.kernel Man page Source code
linear.kernel Man page Source code
memory.ccdf Man page Source code
memory.pdf Man page Source code
power.kernel Man page Source code
pred.cascade Man page Source code
seismic Man page
seismic-package Man page
tweet Man page

Files

NAMESPACE
data
data/tweet.rda
R
R/tweetfunctions.R
MD5
DESCRIPTION
man
man/pred.cascade.Rd
man/get.infectiousness.Rd
man/seismic.Rd
man/tweet.Rd
man/memory.pdf.Rd
man/linear.kernel.Rd
seismic documentation built on May 20, 2017, 2 a.m.