sts (version 1.4)

topicSemanticCoherence: Compute Semantic Coherence

Description

Calculates semantic coherence for an STS model.

Usage

topicSemanticCoherence(object, corpus, M = 10)

Value

a numeric vector containing semantic coherence for each topic

Arguments

object

Model output from sts

corpus

The document term matrix to be modeled in a sparse term count matrix with one row per document and one column per term. The object must be a list of with each element corresponding to a document. Each document is represented as an integer matrix with two rows, and columns equal to the number of unique vocabulary words in the document. The first row contains the 1-indexed vocabulary entry and the second row contains the number of times that term appears. This is the same format in the stm package.

M

the number of top words to consider per topic

Examples

# \donttest{
#An example using the Gadarian data from the stm package.  From Raw text to 
# fitted model using textProcessor() which leverages the tm Package
library("tm"); library("stm"); library("sts")
temp<-textProcessor(documents=gadarian$open.ended.response,
metadata=gadarian, verbose = FALSE)
out <- prepDocuments(temp$documents, temp$vocab, temp$meta, verbose = FALSE)
out$meta$noTreatment <- ifelse(out$meta$treatment == 1, -1, 1)
## low max iteration number just for testing
sts_estimate <- sts(~ treatment*pid_rep, ~ noTreatment, out, K = 3, maxIter = 2, verbose = FALSE)
topicSemanticCoherence(sts_estimate, out)
# }