Twitter Topic Modeling and Visualization for R
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 STM models. Comes with visualizing capabilities like tweet and hashtag maps
and built-in support for 'LDAvis'.
jsonlite, stats, plyr, stopwords, stringr, dplyr, readr,
magrittr, rtweet, quanteda, quanteda.textstats, topicmodels,
stm, tidyr, rlang, maps
rmarkdown, knitr, leaflet, tidytext, modeltools, LDAvis, tm,
ldatuning, stringi, servr,

c(
person("Andreas", "Buchmueller", email = "a.buchmueller@stud.uni-goettingen.de", role = c("aut", "cre"),
comment = "github.com/abuchmueller"),
person("Gillian", "Kant", email = "gillian.kant@stud.uni-goettingen.de", role = c("aut", "ths"),
comment = c(ORCID = "0000-0003-2346-2841")),
person("Christoph", "Weisser", email = "c.weisser@uni-goettingen.de", role = c("aut", "ths"),
comment = c(ORCID = "0000-0003-0616-1027")),
person("Benjamin", "Saefken", email = "benjamin.saefken@uni-goettingen.de", role = c("aut", "ths"),
comment = c(ORCID = "0000-0003-4702-3333")),
person("Thomas", "Kneib", email = "thomas.kneib@wiwi.uni-goettingen.de", role = c("rev", "ths", "dgs"),
comment = c(ORCID = "0000-0003-3390-0972")),
person("Krisztina", "Kis-Katos", email = "krisztina.kis-katos@uni-goettingen.de", role = "rev",
comment = c(ORCID = "0000-0003-2459-1274")))
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'.
jsonlite, stats, plyr, stopwords, stringr, dplyr, readr,
magrittr, rtweet, quanteda, quanteda.textstats, topicmodels,
stm, tidyr, rlang, maps, LDAvis, leaflet, ldatuning, stringi,
tm
rmarkdown, knitr, tidytext, modeltools, servr
Andreas Buchmueller [aut, cre] (github.com/abuchmueller),
Gillian Kant [aut, ths] (<https://orcid.org/0000-0003-2346-2841>),
Christoph Weisser [aut, ths] (<https://orcid.org/0000-0003-0616-1027>),
Benjamin Saefken [aut, ths] (<https://orcid.org/0000-0003-4702-3333>),
Thomas Kneib [rev, ths, dgs] (<https://orcid.org/0000-0003-3390-0972>),
Krisztina Kis-Katos [rev] (<https://orcid.org/0000-0003-2459-1274>)