pred.cascade: Predict the popularity of information cascade

In seismic: Predict Information Cascade by Self-Exciting Point Process

Predict the popularity of information cascade

Description

Predict the popularity of information cascade

Usage

pred.cascade(
  p.time,
  infectiousness,
  share.time,
  degree,
  n.star = 100,
  features.return = FALSE
)

Arguments

p.time	equally spaced vector of time to estimate the infectiousness, p.time[1]=0
infectiousness	a vector of estimated infectiousness, returned by get.infectiousness
share.time	observed resharing times, sorted, share.time[1] =0
degree	observed node degrees
n.star	the average node degree in the social network
features.return	if TRUE, returns a matrix of features to be used to further calibrate the prediction

Value

a vector of predicted populatiry at each time in p.time.

Examples

data(tweet)
pred.time <- seq(0, 6 * 60 * 60, by = 60)
infectiousness <- get.infectiousness(tweet[, 1], tweet[, 2], pred.time)
pred <- pred.cascade(pred.time, infectiousness$infectiousness, tweet[, 1], tweet[, 2], n.star = 100)
plot(pred.time, pred)

seismic documentation built on May 21, 2022, 1:05 a.m.