Package: Twitmo 0.1.5
Andreas Buchmueller
Twitmo: 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 structural topic models (STM). Comes with visualizing capabilities like tweet and hashtag maps and built-in support for 'LDAvis'.
Authors:
Twitmo_0.1.5.tar.gz
Twitmo_0.1.5.tar.gz(r-4.4-noble)
Twitmo_0.1.5.tgz(r-4.4-emscripten)Twitmo_0.1.5.tgz(r-4.3-emscripten)
Twitmo.pdf |Twitmo.html✨
Twitmo/json (API)
NEWS
# Install 'Twitmo' in R: |
install.packages('Twitmo', repos = c('https://abuchmueller.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/abuchmueller/twitmo/issues
ctmgeospatialldanlpstmtopic-modelingtwittertwitter-api
Last updated 2 years agofrom:024ce192e7. Checks:OK: 1. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 05 2024 |
Exports:%>%cluster_tweetsfilter_tweetsfind_ldafind_stmfit_ctmfit_ldafit_stmget_tweetslda_distributionlda_hashtagslda_termsload_tweetsplot_hashtagplot_tweetspool_tweetspredict_ldato_ldavis
Dependencies:askpassbase64encBHbitbit64bslibcachemclicliprcodetoolscolorspacecpp11crayoncrosstalkcurldata.tabledigestdplyrevaluatefansifarverfastmapfastmatchfontawesomeforeachfsgenericsggplot2glmnetgluegmpgtablehighrhmshtmltoolshtmlwidgetshttrhttr2isobandISOcodesiteratorsjquerylibjsonliteknitrlabelinglatticelazyevalldaldatuningLDAvisleafletleaflet.providerslifecyclemagrittrmapsMASSMatrixmatrixStatsmemoisemgcvmimemodeltoolsmunsellnlmeNLPnsyllableopensslpillarpkgconfigplyrpngprettyunitsprogressproxyproxyCpurrrquadprogquantedaquanteda.textstatsR6rappdirsrasterRColorBrewerRcppRcppArmadilloRcppEigenreadrreshape2RJSONIOrlangrmarkdownRmpfrrtweetsassscalesshapeslamSnowballCspstmstopwordsstringistringrsurvivalsysterratibbletidyrtidyselecttinytextmtopicmodelstzdbutf8vctrsviridisLitevroomwithrxfunxml2yaml
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Cluster tweets on an interactive map | cluster_tweets |
Filter tweets | filter_tweets |
Find best LDA model | find_lda |
Find best STM/CTM | find_stm |
Fit CTM (Correlated topic model) | fit_ctm |
Fit LDA Topic Model | fit_lda |
Fit STM (Structural topic model) | fit_stm |
Sample tweets by streaming or searching | get_tweets |
View distribution of fitted LDA Models | lda_distribution |
View Documents (hashtags) heavily associated with topics | lda_hashtags |
View Terms heavily associated with each topic | lda_terms |
Converts Twitter stream data (JSON file) into parsed data frame | load_tweets |
Plot tweets containing certain hashtag | plot_hashtag |
Plot tweets on a static map | plot_tweets |
Prepare Tweets for topic modeling by pooling | pool_tweets |
Predict topics of tweets using fitted LDA model | predict_lda |
Create interactive visualization with LDAvis | to_ldavis |