Analyze and Visualize Word Co-occurrence Networks

This function creates a word co-occurrence network based on a document-feature matrix (dfm).

Usage

word_co_occurrence_network(
  dfm_object,
  co_occur_n = 130,
  top_node_n = 30,
  height = 800,
  width = 900
)

Arguments

dfm_object

A quanteda document-feature matrix (dfm).

co_occur_n

Minimum number of co-occurrences for filtering terms (default is 130).

top_node_n

Number of top nodes to display (default is 30).

height

The height of the resulting Plotly plot, in pixels. Defaults to 800.

width

The width of the resulting Plotly plot, in pixels. Defaults to 900.

Value

A list containing a Plotly object and a data frame with the results.

Examples

if (interactive()) {
  df <- TextAnalysisR::SpecialEduTech
  united_tbl <- TextAnalysisR::unite_text_cols(df, listed_vars = c("title", "keyword", "abstract"))
  tokens <- TextAnalysisR::preprocess_texts(united_tbl, text_field = "united_texts")
  dfm_object <- quanteda::dfm(tokens)
  word_co_occurrence_network_results <- TextAnalysisR::word_co_occurrence_network(
                                        dfm_object,
                                        co_occur_n = 130,
                                        top_node_n = 30,
                                        height = 800,
                                        width = 900)
  word_co_occurrence_network_results$plot
  word_co_occurrence_network_results$table
  word_co_occurrence_network_results$summary
}