cwsForClusters: Map context words and HDBSCAN clusters

In montesmariana/semcloud: Post-processing of token-level clouds

Map context words and HDBSCAN clusters

Description

The function expects a dataframe where at least you have token-id's (e.g. _id), a column with character vectors of context words (e.g. cws) and a column with names of clusters (e.g. cluster). The example below shows how to also turn ;-separated values into character vectors within a tibble dataframe.

Usage

cwsForClusters(variables, cws_column, cluster_column, b = 1)

Arguments

variables	Dataframe with IDs, clusters and lists of context words
cws_column	Character string: Name of the column with the character vectors (one per row) of context words
cluster_column	Character string: Name of the column with the name of the clusters (must be a factor)
b	Weight for computing fscore

Value

a tibble with one row per context word per cluster, with frequency information.

Examples

## Not run: 

variables <- dplyr::mutate(variables, cws = stringr::str_split(cws, ";"))
cwsForClusters(variables, "cws", "cluster")


## End(Not run)

montesmariana/semcloud documentation built on April 15, 2022, 6:57 a.m.