# Methods and Measures for Semantic Network Analysis

## Documentation for package ‘SemNeT’ version 1.4.5

- DESCRIPTION file.
- Package NEWS.

## Help Pages

SemNeT-package | SemNeT-package
animals.freq | Frequency of Animal Responses
ASPL | Average Shortest Path Length
bootSemNeT | Bootstrapped Semantic Network Analysis
CC | Clustering Coefficient
CN | Community Network Estimation
compare_nets | Plots Networks for Comparison
convert2cytoscape | Convert Adjacency Matrix to Cytoscape Format
convert2igraph | Convert Network(s) to igraph's Format
equate | Equate Groups
finalize | Finalize Response Matrix
net.high | High Openness to Experience Network
net.low | Low Openness to Experience Network
NRW | Naive Random Walk Network Estimation
one.result | Simulated Result for Dataset One
open.binary | Binary response Matrices (Openness and Verbal Fluency)
open.clean | Cleaned response Matrices (Openness and Verbal Fluency)
open.group | Groups for Openness and Verbal Fluency
PF | Pathfinder Network
plot.animateShiny | Animate Networks for Spreading Activation from Shiny
plot.bootSemNeT | Plot for bootSemNeT
plot.compareShiny | Plots Networks for Comparison from Shiny
Q | Modularity
randnet.test | Test Against Random Networks
randwalk | Random Walk Simulation
response.analysis | Response Analysis
SemNeT | SemNeT-package
semnetmeas | Semantic Network Measures
SemNeTShiny | Shiny App for 'SemNeT'
sim.fluency | Simulates a verbal fluency binary response matrix
similarity | Measures of Similarity
test.bootSemNeT | Statistical tests for 'bootSemNeT'
TMFG | Triangulated Maximally Filtered Graph
two.result | Simulated Result for Dataset One and Two
vignette.plots | Plots for Vignette