write_cluster_text: Write/Read Cluster Text for Human Categorization

In trinker/clustext: Consistent Clustering for Text Data

Description

Write cluster text from get_text(assign_cluster(myfit)) to an external file for categorization. After file has been written with write_cluster_text a human coder can assign categories to each cluster. Simple write the category after the Cluster #:. To set a cluster category equal to another simply write and equal sign follwed by the other cluster to set as the same category (e.g., Cluster 10: =5 to set cluster #10 the same as cluster #5). See readLines(system.file("additional/foo_turk.txt", package = "clustext")) for an example.

Usage

write_cluster_text(x, path, n.sample = NULL, lead = " * ", ...)

read_cluster_text(path, ...)

Arguments

x	An assign_cluster object.
path	A pather to the file (.txt) is recommended.
n.sample	The length to limit the sample to (default gives all text in the cluster). Setting this to an integer uses this as the number to randomly sample from.
lead	A leading character string prefix to give the cluster text.
...	ignored.

See Also

categorize

Examples

library(dplyr)

## Assign Clusters
ca <- presidential_debates_2012 %>%
    with(data_store(dialogue)) %>%
    hierarchical_cluster() %>%
    assign_cluster(k = 7)

## Write Cluster Text for Human Categorization
write_cluster_text(ca)
write_cluster_text(ca, n.sample=10)
write_cluster_text(ca, lead="  -", n.sample=10)

## Read Human Coded Categories Back In
categories_file <- system.file("additional/foo_turk.txt", package = "clustext")
readLines(categories_file)
(categories_key <- read_cluster_text(categories_file))

## Add Categories Back to Original Data Set
categorize(
    data = presidential_debates_2012,
    assign.cluster = ca,
    cluster.key = categories_key
)

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