stm: toLDAvisJson – R documentation

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stm

toLDAvisJson

Wrapper to create Json mapping for LDAvis. This can be useful in indirect render e.g. Shiny Dashboards

Description

Tool for exploring topic/word distributions using LDAvis topic browser.

Usage

toLDAvisJson(
  mod,
  docs,
  R = 30,
  plot.opts = list(xlab = "PC1", ylab = "PC2"),
  lambda.step = 0.1,
  reorder.topics = TRUE
)

Arguments

`mod`	STM object. Output from stm function.
`docs`	Documents object passed to `stm` in this package's standard format (see the documentation in `stm`.
`R`	Passed to `createJSON` "integer, the number of terms to display in the barcharts of the interactive viz. Default is 30. Recommended to be roughly between 10 and 50."
`plot.opts`	Passed to `createJSON` "a named list used to customize various plot elements. By default, the x and y axes are labeled 'PC1' and 'PC2' (principal components 1 and 2), since jsPCA is the default scaling method. "
`lambda.step`	Passed to `createJSON` "a value between 0 and 1. Determines the interstep distance in the grid of lambda values over which to iterate when computing relevance. Default is 0.01. Recommended to be between 0.01 and 0.1."
`reorder.topics`	Passed to `createJSON` "Should LDAvis re-order the K topics in order of decreasing proportion? Default is True"

Details

Tool for exploring topic/word distributions using LDAvis topic browser. Development build of LDAvis available at https://github.com/cpsievert/LDAvis or download from CRAN. Note: LDAvis may renumber the topics.

References

Carson Sievert and Kenny Shirley. LDAvis: Interactive Visualization of Topic Models. R package version 0.3.1. https://github.com/cpsievert/LDAvis

Examples

mod <- stm(poliblog5k.docs, poliblog5k.voc, K=25,
           prevalence=~rating, data=poliblog5k.meta,
           max.em.its=2, init.type="Spectral") 
#please don't run a model with 2 iterations
#this is done here to make it run quickly.
toLDAvisJson(mod=mod, docs=poliblog5k.docs)

stm

Estimation of the Structural Topic Model

v1.3.6

MIT + file LICENSE

Authors

Margaret Roberts [aut], Brandon Stewart [aut, cre], Dustin Tingley [aut], Kenneth Benoit [ctb]

Initial release