VOSONDash is an interactive R Shiny web application for the visualisation and analysis of social network data. The app has a dashboard layout with sections for visualising and manipulating network graphs, performing text analysis, displaying network metrics and the collection of network data using the vosonSML R package.
VOSONDash is an R package and must be installed before the app can be run.
Install the latest release on CRAN (v0.5.7):
Install the latest release via GitHub (v0.5.7):
install.packages( pkgs = "https://github.com/vosonlab/VOSONDash/releases/download/v0.5.7/VOSONDash-0.5.7.tar.gz", repo = NULL, type = "source")
Install the latest development version (v0.5.8.9000):
Once the VOSON Dashboard package is installed and loaded the Shiny web application can be run from the RStudio console using the
Running the app for the first time
When run the
VOSONDash app will check that all of the R packages that are required to make it work are installed. It is likely that some packages will be missing and the app will print a message indicating the missing packages and a command that can be used to install them.
> runVOSONDash() ================================================= VOSONDash v0.5.8 ... Checking packages... Error: Required packages missing. - shinyjs - visNetwork Please install required packages before using VOSONDash: install.packages(c("shinyjs", "visNetwork"))
The missing packages can be installed using the above
After installing required packages and running again the
VOSONDash Shiny app will open up in the default web browser.
Network and text analysis of graph data.
- Network Graphs: Visualise and modify networks
- Network Metrics: Calculate node and network level metrics
- Text Analysis: Word frequency, word clouds and sentiment
- Assortativity: Calculate homogeneity and homophily indexes (if VOSON categorical node attributes present)
Figure 1. Environmental activist site hyperlink network loaded from a
graphml file and plotted by the
Collection and Network Creation
Graphical interfaces for collecting network data from social media API's.
- Collect: Twitter, youtube and reddit network data
- Create: different types of networks from the data such as activity, actor, twomode and semantic networks
Figure 2. Collection of recent
#auspol tweets and generation of an actor network with the
Figure 3. Create an actor network and add tweet text to the network.
API Keys and Tokens
- API Keys: Enter, save, load API keys and create access tokens
Figure 4. Twitter API token creation and selection.
This application would not be possible without key packages by other authors in the R community, particularly the shiny, shinydashboard, DT and shinyjs packages. Graph visualisations created with igraph and visNetwork, and text analysis with support from tm, SnowballC, wordcloud and syuzhet packages.