Package: seismic 1.1

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.

Authors:Hera He, Murat Erdogdu, Qingyuan Zhao

seismic_1.1.tar.gz
seismic_1.1.zip(r-4.5)seismic_1.1.zip(r-4.4)seismic_1.1.zip(r-4.3)
seismic_1.1.tgz(r-4.4-any)seismic_1.1.tgz(r-4.3-any)
seismic_1.1.tar.gz(r-4.5-noble)seismic_1.1.tar.gz(r-4.4-noble)
seismic_1.1.tgz(r-4.4-emscripten)seismic_1.1.tgz(r-4.3-emscripten)
seismic.pdf |seismic.html
seismic/json (API)

# Install 'seismic' in R:
install.packages('seismic', repos = c('https://qingyuanzhao.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/qingyuanzhao/seismic/issues

Datasets:
  • tweet - An example information cascade

On CRAN:

2 exports 0.93 score 0 dependencies 1 mentions 241 downloads

Last updated 2 years agofrom:1e587e72e5. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 26 2024
R-4.5-winOKAug 26 2024
R-4.5-linuxOKAug 26 2024
R-4.4-winOKAug 26 2024
R-4.4-macOKAug 26 2024
R-4.3-winOKAug 26 2024
R-4.3-macOKAug 26 2024

Exports:get.infectiousnesspred.cascade

Dependencies: