Tailored for topic modeling with tweets and fit for visualization tasks in R.
Collect, pre-process and analyze the contents of tweets using
LDA and structural topic models (STM). Comes with visualizing capabilities like tweet and hashtag maps
and built-in support for 'LDAvis'.
| Version: |
0.1.2 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
jsonlite, stats, plyr, stopwords, stringr, dplyr, readr, magrittr, rtweet, quanteda, quanteda.textstats, topicmodels, stm, tidyr, rlang, maps, LDAvis, leaflet, ldatuning, stringi, tm |
| Suggests: |
rmarkdown, knitr, tidytext, modeltools, servr |
| Published: |
2021-12-06 |
| DOI: |
10.32614/CRAN.package.Twitmo |
| Author: |
Andreas Buchmueller [aut, cre] (github.com/abuchmueller),
Gillian Kant 
[aut, ths],
Christoph Weisser
[aut, ths],
Benjamin Saefken
[aut, ths],
Thomas Kneib
[rev, ths, dgs],
Krisztina Kis-Katos
[rev] |
| Maintainer: |
Andreas Buchmueller <a.buchmueller at stud.uni-goettingen.de> |
| BugReports: |
https://github.com/abuchmueller/Twitmo/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://github.com/abuchmueller/Twitmo |
| NeedsCompilation: |
no |
| Materials: |
README NEWS |
| CRAN checks: |
Twitmo results |