README.md

In wilryh/parrot: Text Scaling for Open-Ended Survey Responses

parrot

Parrot scales short text around common words.

Let me know if you run into any problems.

Paper: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3044864

The scale_text function suggests a truncation for the SVD. It produces approximately the same number of pivot words.

Example

```{r example}

## packages installed in install_github(, dependencies=TRUE)

install.packages(c("stm","ggplot2","gridExtra","Matrix","reshape2","ForeCA","devtools","magrittr","RSpectra"))

## word embeddings

install.packages(c("dplyr","readr","tidyr","CCA"))

## optional (not installed)

install.packages(c("knitr"))

library(devtools) install_github("wilryh/parrot", dependencies=TRUE)

library(stm) library(parrot)

processed <- textProcessor( input_data$text, data.frame(input_data), removestopwords=T, lowercase=T, stem=F ) out <- prepDocuments( processed$documents, processed$vocab, processed$meta )

tdm <- doc_to_tdm(out)

embeddings <- read_word_embeddings( in_vocab=out$vocab, ovefile = "O2M_overlap.txt" # must add location on your computer "path/to/O2M_overlap.txt" ## ovefile2 = "path/to/O2M_oov.txt", # very rare words and misspellings ## available here http://www.cis.uni-muenchen.de/~wenpeng/renamed-meta-emb.tar.gz ## must unpack and replace "path/to/" with location on your computer )

scores <- scale_text( meta=out$meta, tdm=tdm

embeddings=embeddings[["meta"]], ## embeddings have little effect

on output -- if used, consider setting pivot lower (e.g. pivot = 1/2)

)

document_scores <- score_documents( scores=scores, n_dimensions=10 )

get_keywords(scores, n_dimensions=3, n_words=15)

with(document_scores, cor(sqrt(n_words), X0, use="complete"))

plot_keywords( scores, x_dimension=1, y_dimension=2, q_cutoff=0.9 ) ```

wilryh/parrot documentation built on Jan. 9, 2020, 2:16 p.m.