Docker Standalone Version
The standalone version includes everything to run the application. This includes the app’s R Shiny code together with the required libraries, a Shiny Server, an RStudio Server, a MariaDB database and a solr server.
In order to run the standalone version of the application the installation of docker is required. Check out https://docs.docker.com/install/ for more details on how to do this.
Start the application
The application is hosted at dockerhub. If you run the following command in a Terminal, the image will be pulled and started afterwards.
docker run -d -p 3838:3838 -p 8787:8787 -p 8983:8983 ckahmann/ilcm:latest
latest will pull the most recently uploaded version of the image.
ckahmann/ilcm:latest a specific version can be specified. For example:
ckahmann/ilcm:0.998 will pull the Version 0.998 from dockerhub.
If this process has succeeded, 3 services are accessible to the user. Per default they use the the ports: 3838, 8787 and 8983.
Access the services
You can access the services using a browser.
Additional configuration can be set while executing the docker run command.
If some of the defaults ports are alerady used on you system you can change them during the start up process of the application. To do this, the port mapping are set via -p during the docker run command.
docker run -it -d -p 3666:3838 -p 3667:8787 -p 3668:8983 ckahmann/ilcm:latest
will map the applications to the ports: 3666, 3667 and 3668.
You can specify your own named volumes using the -v parameter. The database is stored at
/var/lib/mysql, the Shiny Application for the RStudio and Shiny Server at
/home/rstudio/ilcm and the solr data at
docker run -it -d -v ilcm_database:/var/lib/mysql ckahmann/ilcm:latest
will create a named volume called ilcm_database storing the internal state of application’s database.
The application has been tested using Chrome.
tmca (Text Mining for Content Analysis) for R
The LCM is based on a library providing basic processing abstractions for text mining. Especially the application of text mining to social science content analysis is reflected in this library. The library is a basically a wrapper around quanteda, R spaCy, lda, liblineaR and many more in order to provide a convenient and methodologically sound access to those tools. The reprository can be found here:
The visual access to the toolsets of the tmca package are integrated into a R Shiny App.This is hosted at https://github.com/ChristianKahmann/ilcm_Shiny. Feel free to check out the latest changes and report issues or feature requests.