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SemNeT (version 1.4.4)

Methods and Measures for Semantic Network Analysis

Description

Implements several functions for the analysis of semantic networks including different network estimation algorithms, partial node bootstrapping (Kenett, Anaki, & Faust, 2014 ), random walk simulation (Kenett & Austerweil, 2016 ), and a function to compute global network measures. Significance tests and plotting features are also implemented.

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Install

install.packages('SemNeT')

Monthly Downloads

320

Version

1.4.4

License

GPL (>= 3.0)

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Repository

https://github.com/AlexChristensen/SemNeT

Maintainer

Alexander Christensen

Last Published

August 12th, 2023

Functions in SemNeT (1.4.4)

plot.compareShiny

Plots Networks for Comparison from Shiny

High Openness to Experience Network

Test Against Random Networks

Simulated Result for Dataset One and Two

plot.bootSemNeT

Plot for bootSemNeT

Cleaned response Matrices (Openness and Verbal Fluency)

Groups for Openness and Verbal Fluency

plot.animateShiny

Animate Networks for Spreading Activation from Shiny

Plots for Vignette

Simulates a verbal fluency binary response matrix

Semantic Network Measures

Random Walk Simulation

response.analysis

Response Analysis

Binary response Matrices (Openness and Verbal Fluency)

Measures of Similarity

test.bootSemNeT

Statistical tests for bootSemNeT

Average Shortest Path Length

Triangulated Maximally Filtered Graph

Pathfinder Network

Naive Random Walk Network Estimation

Shiny App for SemNeT

Community Network Estimation

Frequency of Animal Responses

Clustering Coefficient

SemNeT--package

Plots Networks for Comparison

Finalize Response Matrix

Bootstrapped Semantic Network Analysis

Simulated Result for Dataset One

Low Openness to Experience Network

convert2cytoscape

Convert Adjacency Matrix to Cytoscape Format

Convert Network(s) to igraph's Format