multiple_netfacs_network {NetFACS} | R Documentation |
Creates network objects out of the netfacs data
Description
Takes the results of the nefacs object for combinations of 2 elements and
turns them into a network object (class igraph
and
tbl_graph
) that can be used for further plotting and analyses
Usage
multiple_netfacs_network(
netfacs.list,
link = "unweighted",
significance = 0.01,
min.count = 1,
min.prob = 0,
ignore.element = NULL
)
multiple.netfacs.network(
netfacs.list,
link = "unweighted",
significance = 0.01,
min.count = 1,
min.prob = 0,
ignore.element = NULL
)
Arguments
netfacs.list |
list of multiple objects resulting from
|
link |
determines how nodes/elements are connected. 'unweighted' gives a 1 to significant connections and 0 to all others; 'weighted' gives the difference between observed and expected probability of co-occurrence; 'raw' just uses the observed probability of co-occurrence; 'SRI' uses the simple ratio index/affinity (probability of co-occurrence/ (probabilities of each element and the combination)) |
significance |
numeric value, determining the p-value below which combinations are considered to be dissimilar enough from the null distribution |
min.count |
numeric value, suggesting how many times a combination should at least occur to be displayed |
min.prob |
numeric value, suggesting the probability at which a combination should at least occur to be displayed |
ignore.element |
vector of elements that will not be considered for the network, e.g. because they are too common or too rare or their interpretation is not relevant here |
Value
Function returns a network object where the nodes are the elements, edges represent their co-occurrence, and the vertex and edge attributes contain all additional information from the netfacs object
Examples
data(emotions_set)
emo.faces <- netfacs_multiple(
data = emotions_set[[1]],
condition = emotions_set[[2]]$emotion,
ran.trials = 10, # only for example
combination.size = 2
)
emo.nets <- multiple_netfacs_network(emo.faces)