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influential  

Identification and Classification of the Most Influential Nodes
View on CRAN: Click here


Download and install influential package within the R console
Install from CRAN:
install.packages("influential")

Install from Github:
library("remotes")
install_github("cran/influential")

Install by package version:
library("remotes")
install_version("influential", "2.3.2")



Attach the package and use:
library("influential")
Maintained by
Adrian Salavaty
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-02-17
Latest Update: 2023-12-09
Description:
Contains functions for the classification and ranking of top candidate features, reconstruction of networks from adjacency matrices and data frames, analysis of the topology of the network and calculation of centrality measures, and identification of the most influential nodes. Also, a function is provided for running SIRIR model, which is the combination of leave-one-out cross validation technique and the conventional SIR model, on a network to unsupervisedly rank the true influence of vertices. Additionally, some functions have been provided for the assessment of dependence and correlation of two network centrality measures as well as the conditional probability of deviation from their corresponding means in opposite direction. Fred Viole and David Nawrocki (2013, ISBN:1490523995). Csardi G, Nepusz T (2006). "The igraph software package for complex network research." InterJournal, Complex Systems, 1695. Adopted algorithms and sources are referenced in function document.
How to cite:
Adrian Salavaty (2020). influential: Identification and Classification of the Most Influential Nodes. R package version 2.3.2, https://cran.r-project.org/web/packages/influential. Accessed 08 Oct. 2026.
Previous versions and publish date:
(2026-10-07 01:20), 0.1.0 (2020-02-17 15:50), 1.0.0 (2020-04-25 09:30), 1.1.0 (2020-06-23 12:40), 1.1.1 (2020-06-24 10:20), 1.1.2 (2020-06-26 16:50), 2.0.0 (2020-09-25 15:20), 2.0.1 (2020-11-20 06:20), 2.2.0 (2021-04-18 04:10), 2.2.1 (2021-04-24 13:30), 2.2.2 (2021-04-30 12:10), 2.2.3 (2021-07-17 14:40), 2.2.4 (2021-11-01 06:40), 2.2.5 (2022-04-14 16:02), 2.2.6 (2022-08-06 09:30), 2.2.7 (2023-05-16 07:10), 2.2.8 (2023-11-19 06:10), 2.2.9 (2023-12-09 09:20), 2.3.0 (2026-02-13 08:00), 2.3.1 (2026-05-28 15:20), 2.3.2 (2026-08-23 14:30)
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