as_topic: Convert 'get_terms' to Topics

In trinker/clustext: Consistent Clustering for Text Data

Description

View important terms as a comma separated string (a topic).

Usage

as_topic(x, max.n = 8, sort = TRUE, ...)

## S3 method for class 'get_terms'
as_topic(x, max.n = 8, sort = TRUE, ...)

Arguments

x	A get_terms object.
max.n	The max number of words to show before truncation.
sort	logical. If TRUE the cluster topics are sorted by size (number of documents) otherwise the topics are sorted by cluster number.
...	ignored.

Value

Returns a data.frame of "cluster", "count", and "terms". Pretty prints as clusters, number of documents, and associated important terms.

Examples

library(dplyr)

myfit5 <- presidential_debates_2012 %>%
    mutate(tot = gsub("\\..+$", "", tot)) %>%
    textshape::combine() %>%
    filter(person %in% c("ROMNEY", "OBAMA")) %>%
    with(data_store(dialogue, stopwords = tm::stopwords("english"), min.char = 3)) %>%
    hierarchical_cluster()

ca5 <- assign_cluster(myfit5, k = 50)

get_terms(ca5, .4) %>%
    as_topic()

get_terms(ca5, .4) %>%
    as_topic(sort=FALSE)

get_terms(ca5, .95) %>%
    as_topic()

trinker/clustext documentation built on May 31, 2019, 8:41 p.m.