{"id":25290542,"url":"https://github.com/wesslen/topic-modeling-workshop-with-r","last_synced_at":"2025-10-27T23:31:24.174Z","repository":{"id":81790257,"uuid":"81484754","full_name":"wesslen/Topic-Modeling-Workshop-with-R","owner":"wesslen","description":"A workshop on analyzing topic modeling (LDA, CTM, STM) using R","archived":false,"fork":false,"pushed_at":"2018-03-01T06:14:00.000Z","size":27267,"stargazers_count":51,"open_issues_count":0,"forks_count":14,"subscribers_count":7,"default_branch":"master","last_synced_at":"2024-10-28T03:39:55.800Z","etag":null,"topics":["lda","r","stm","topic-modeling"],"latest_commit_sha":null,"homepage":null,"language":"HTML","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/wesslen.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null}},"created_at":"2017-02-09T19:06:50.000Z","updated_at":"2022-06-20T01:42:02.000Z","dependencies_parsed_at":null,"dependency_job_id":"a06c48e2-d352-4611-a23c-b7f357eda0be","html_url":"https://github.com/wesslen/Topic-Modeling-Workshop-with-R","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/wesslen%2FTopic-Modeling-Workshop-with-R","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/wesslen%2FTopic-Modeling-Workshop-with-R/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/wesslen%2FTopic-Modeling-Workshop-with-R/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/wesslen%2FTopic-Modeling-Workshop-with-R/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/wesslen","download_url":"https://codeload.github.com/wesslen/Topic-Modeling-Workshop-with-R/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":238571619,"owners_count":19494253,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["lda","r","stm","topic-modeling"],"created_at":"2025-02-13T00:26:43.291Z","updated_at":"2025-10-27T23:31:20.665Z","avatar_url":"https://github.com/wesslen.png","language":"HTML","funding_links":[],"categories":[],"sub_categories":[],"readme":"## Set up\n\n1.  Download the materials in this repository using the \"Clone or download\" button and click the \"Download ZIP\" link. Unzip the file locally.\n\n2.  Ensure you have [R](http://archive.linux.duke.edu/cran/) and [R Studio](https://www.rstudio.com/products/rstudio/download/) installed on your machine. Use the links and follow the instructions to download each locally.\n\nAlternatively, you can use [RollApp](https://www.rollapp.com/) to create a free account and run R and R Studio on a cloud service. This option has more issues with saving so this is only an option if you want to avoid downloading R/R Studio locally.\n\nOpen R Studio and run the following command to ensure you have all of the R libraries:\n\n```{r}\npackages \u003c- c(\"quanteda\",\"tidyverse\",\"topicmodels\",\"stm\",\"RColorBrewer\",\"servr\", \n                \"LDAvis\", \"RJSONIO\", \"igraph\",\"visNetwork\")\n\nlapply(packages, install.packages(packages), character.only = TRUE)\n```\n\n## Code\n\n| Part | Subject                           |        |           |\n| ---- | --------------------------------- | ------ | --------- |\n|    1 | Latent Dirichlet Allocation (LDA) | [code](/part1-lda.Rmd) | [HTML output](https://htmlpreview.github.io/?https://github.com/wesslen/Topic-Modeling-Workshop-with-R/blob/master/part1-lda.html)   |\n|    2 | Correlated Topic Model (CTM)      | [code](/part2-ctm.Rmd) | [HTML output](https://rawgit.com/wesslen/Topic-Modeling-Workshop-with-R/master/part2-ctm.html)   |\n|    3 | Structured Topic Model (STM)      | [code](/part3-stm.Rmd) | [HTML output](https://htmlpreview.github.io/?https://github.com/wesslen/Topic-Modeling-Workshop-with-R/blob/master/part3-stm.html)   |\n\n\nFor users interested in large-scale LDA on Spark (not available yet for CTM or STM), see [this code](https://github.com/wesslen/Code-Tutorials-for-SOPHI/blob/master/code/Scala-LDA.md).\n\nUsers interested in Structural Topic Modeling should read [www.structuraltopicmodel.com](http://www.structuraltopicmodel.com/). This site provides multiple papers that have employed STM as well as references on STM including the `stm` R package.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fwesslen%2Ftopic-modeling-workshop-with-r","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fwesslen%2Ftopic-modeling-workshop-with-r","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fwesslen%2Ftopic-modeling-workshop-with-r/lists"}