CN: Community Network Estimation

In SemNeT: Methods and Measures for Semantic Network Analysis

Community Network Estimation

Description

Estimates a semantic network using the Community Network method described in Goni et al. (2011)

Usage

CN(data, window = 2, alpha = 0.05, enrich = FALSE)

Arguments

data	Matrix or data frame. A preprocessed verbal fluency matrix where rows are participants and columns are verbal fluency responses
window	Numeric. Size of window to look for co-occurences in. Defaults to 2
alpha	Numeric. Significance value. Defaults to .05
enrich	Boolean. Should the network be enriched by connecting all nodes in their respective modules? Defaults to FALSE

Value

Returns a undirected semantic network

Author(s)

Alexander Christensen <[e-mail]>

References

Goni, J., Arrondo, G., Sepulcre, J., Martincorena, I., de Mendizabal, N. V., Corominas-Murtra, B., ... & Villoslada, P. (2011). The semantic organization of the animal category: Evidence from semantic verbal fluency and network theory. Cognitive Processing, 12, 183-196.

Examples

# Get data
data <- open.clean

# Organize group data
## Get group data
group <- open.group

## Low and high openness to experience groups
low <- data[which(group == "Low"),]
high <- data[which(group == "High"),]

## Not run: 
# Compute networks
low.net <- CN(low)
high.net <- CN(high)

## End(Not run)

SemNeT documentation built on Aug. 12, 2023, 5:06 p.m.