threshold_graph {memnet} | R Documentation |
Create a graph from verbal fluency data by adding edges for words that occur
adjacent to each other more frequently than min_cooc
.
threshold_graph(dat, min_cooc = 2L)
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. |
A matrix
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.
# 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)