Word co-occurrence network graph

words_cooccur.R

library(tidytext)
library(widyr)
library(igraph)
library(ggraph)

words_cooccur <- tidy_words %>%
    group_by(word) %>%
    filter(n() > 250) %>%
    ungroup() %>%
    pairwise_cor(word, Respondent, sort = TRUE, upper = FALSE) %>%
    filter(correlation > 0.11)
    
word_counts <- tidy_words %>%
    count(word, sort = TRUE) %>%
    filter(word %in% words_cooccur$item1 | word %in% words_cooccur$item2)
    
words_cooccur %>%
    graph_from_data_frame(vertices = word_counts) %>%
    ggraph(layout = "nicely") +
    geom_edge_link(aes(edge_alpha = correlation),
                   edge_width = 0.5, show.legend = FALSE) +
    geom_node_point(aes(size = n),
                    alpha = 0.7) +
    geom_node_text(aes(label = name), repel = TRUE) +
    labs(size = "Number of\nuses") +
    theme_void()