View source: R/netfacs_network.R
netfacs_network | R Documentation |
Takes the results of the nefacs object for combinations of 2 elements and turns them into a network object (igraph) that can be used for further plotting and analyses
netfacs_network( netfacs.data, link = "unweighted", significance = 0.01, min.count = 1, min.prob = 0, ignore.element = NULL ) netfacs.network( netfacs.data, link = "unweighted", significance = 0.01, min.count = 1, min.prob = 0, ignore.element = NULL )
netfacs.data |
object 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 |
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 |
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
data(emotions_set) angry.face <- netfacs( data = emotions_set[[1]], condition = emotions_set[[2]]$emotion, test.condition = "anger", ran.trials = 100, combination.size = 2 ) anger.net <- netfacs_network( netfacs.data = angry.face, link = "unweighted", significance = 0.01, min.count = 1 )
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