All Projects → vosonlab → VOSONDash

vosonlab / VOSONDash

Licence: GPL-3.0 license
R Shiny application for interactive analysis of networks created by vosonSML.

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VOSONDash - Shiny Dashboard App

CRAN_Status_Badge CRAN_Monthly CRAN_Total Github_Release Github_Dev Last_Commit Build_Status

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.

Installation

Install the latest release via CRAN:

install.packages("VOSONDash")

Install the latest release via GitHub:

install.packages("https://api.github.com/repos/vosonlab/VOSONDash/tarball/v0.5.7",
                 repo = NULL, type = "source")

Install the development version:

# library(remotes)
remotes::install_github("vosonlab/VOSONDash")

Once the VOSON Dashboard package is installed and loaded the Shiny web application can be run from the RStudio console using the runVOSONDash() function.

library(VOSONDash)
runVOSONDash()

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.

For example:

runVOSONDash()
# =================================================
# VOSONDash v0.5.11
# ...
# 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 install.packages command.

After installing required packages and running again the VOSONDash Shiny app will open up in the default web browser.

VOSON Dashboard

VOSONDash features an intuitive web interface with a section for ‘Analysis’ of graph data loaded from igraph objects and a section for the ‘Collection’ of social media data using vosonSML.

Analysis

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)

VOSONDash Network Graphs Analysis

Figure 1. Environmental activist site hyperlink network loaded from a graphml file and plotted by the visNetwork package.

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

VOSONDash Twitter Collection

Figure 2. Collection of recent #auspol tweets and generation of an actor network with the vosonSML package.

VOSONDash Twitter Network Creation

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

VOSONDash Keys and Tokens Interface

Figure 4. Twitter API token creation and selection.

Special thanks

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.

Code of Conduct

Please note that the VOSON Lab projects are released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].