fst_concept_network {finnsurveytext} | R Documentation |
Concept Network - Make Concept Network plot
Description
This function takes a string of terms (separated by commas) or a single term and, using 'textrank_keywords()' from 'textrank' package, filters data based on 'pos_filter' and finds words connected to search terms. Then it plots a Concept Network based on the calculated weights of these terms and the frequency of co-occurrences.
Usage
fst_concept_network(
data,
concepts,
threshold = NULL,
norm = "number_words",
pos_filter = NULL,
title = NULL
)
Arguments
data |
A dataframe of text in CoNLL-U format. |
concepts |
List of terms to search for, separated by commas. |
threshold |
A minimum number of occurrences threshold for 'edge' between searched term and other word, default is 'NULL'. Note, the threshold is applied before normalisation. |
norm |
The method for normalising the data. Valid settings are '"number_words"' (the number of words in the responses, default), '"number_resp"' (the number of responses), or 'NULL' (raw count returned). |
pos_filter |
List of UPOS tags for inclusion, default is 'NULL' to include all UPOS tags. |
title |
Optional title for plot, default is 'NULL' and a generic title ("Textrank extracted keyword occurrences") will be used. |
Value
Plot of Concept Network.
Examples
data <- conllu_cb_bullying_iso
con <- "kiusata, lyöminen"
pf <- c("NOUN", "VERB", "ADJ", "ADV")
title <- "Bullying Concept Network"
fst_concept_network(data, concepts = con, pos_filter = pf, title = title)