threshold_graph: Create threshold graph

In memnet: Network Tools for Memory Research

Description

Create a graph from verbal fluency data by adding edges for words that occur adjacent to each other more frequently than min_cooc.

Usage

threshold_graph(dat, min_cooc = 2L)

Arguments

dat	list of character vectors containing the fluency productions.
min_cooc	integer specifying the minimum number of times two words are required to coocur one step apart from each other for an edge to connect those words.

Value

A matrix

References

Wulff, D. U., Hills, T., & Mata, R. (2018, October 29). Structural differences in the semantic networks of younger and older adults. https://doi.org/10.31234/osf.io/s73dp

Zemla, J. C., & Austerweil, J. L. (2018). Estimating semantic networks of groups and individuals from fluency data. Computational Brain & Behavior, 1-23.

Examples

# get animal fluency data
data(animal_fluency)

# infer influence network
inferred_network = threshold_graph(animal_fluency)

# Simulate -----

# generate watts strogatz graph
network = grow_ws(n = 200, k = 10, p = .5)

# generate fluency data
# sets string equal TRUE as community_graph expects mode character
fluency_data = fluency(get_adjlist(network), rep(10, 100), string = TRUE)

# infer fluency network
inferred_network = threshold_graph(fluency_data)

memnet documentation built on May 2, 2019, 9:35 a.m.