Predict the popularity of information cascade

Description

Predict the popularity of information cascade

Usage

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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

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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)