snahelper provides a set RStudio Addin for social
network analysis. The main addin is the SNAhelper which
provides a simple GUI to do common network analytic tasks and visualize
a network with ggraph.
The second addin, called Netbuilder allows you to
quickly build small networks with a small “canvas” to draw on. The
network can be exported as an igraph object at the end of the session by
clicking on “Done”.
The third addin Netreader is meant to facilitated the
import of raw network data. It provides a GUI to easily read network and
attribute data and combine them to an igraph object. The underlying code
of the import procedure is shown at the end. This should help users to
learn importing data themselves.
The fourth addin Componentlayouter allows to layout
networks with several components manually by placing them on an empty
canvas. Components can also be rotated and resized. After finishing the
session, the layout is saved as x and y vertex attributes.
Code to reproduce the used network.
library(tidyverse)
library(igraph)
url <- "https://raw.githubusercontent.com/evelinag/StarWars-social-network/master/networks/starwars-full-interactions-allCharacters.json"
df <- jsonlite::fromJSON(url)
df$nodes$id <- 1:nrow(df$nodes)
df$nodes$display <- df$nodes$name
df$nodes$name <- df$nodes$id-1
g <- graph_from_data_frame(df$links,directed = F,vertices = df$nodes)
V(g)$name <- V(g)$display
g <- remove.vertex.attribute(g,"id")
g <- remove.vertex.attribute(g,"display")
g <- delete.vertices(g,which(degree(g)==0))
V(g)$display <- ifelse(V(g)$value>75,V(g)$name,"")
V(g)$colour <- ifelse(V(g)$display=="",NA,V(g)$display)
gNetreader should be pretty selfexplanatory. The first
two tabs allow you to import raw data (edges and attributes). Make sure
to specify file delimiters, etc. according to the shown preview.
Using the Netreader should comes with a learning effect
(hopefully). The last tab shows the R code to produce the network with
the chosen data without using the Addin. 
The network will be saved in your global environment once you click “Done”.
Highlight an igraph object in your script and selcet the
Componentlayouter from the RStudio addin menu. Components
are added by clicking on the canvas and can be resized/rotated and
re-positioned using the buttons at the bottom. The final layout is
stored as x and y coordinates in the igraph object.
# developer version
#install.packages(remotes)
remotes::install_github("schochastics/snahelper")
#CRAN version
install.packages("snahelper")To work properly, you also need graphlayouts, which adds new layout algorithms.
install.packages("graphlayouts")To use the main addin, simply highlight a network in your script and
select SNAhelper from the Addin dropdown menu.
The layout tab allows you to choose from all implemented algorithms
in igraph and some layouts from graphlayouts.
The default is a stress based layout and also the recommended choice.
See my
blog for an explanation. In the tweak section you can move
individual nodes around. Choose the node from the dropdown menu and
click on its new position in the plot.
The Node Attribute Manager shows all existing node attributes in a sortable table. In addition, you can calculate some new ones (centrality and clustering). The functions automatically choose the right version of indices, depending if the network is directed/weighted/undirected/unweighted.
This is where you can style your nodes. You can either do it manually, by choosing a color/size for all nodes together, or based on an attribute.
Same as Node Attribute Manager but for edges. So far only shows existing edge attributes.
You can style your edges here. snahelper automatically
detects if your network is directed and adds arrows if the network is
directed. The other options are similar to the nodes tab. The snahelper
automatically chooses the appropriate edge geom. If multiple edges are
present, it uses geom_edge_parallel0(). Otherwise
geom_edge_link0().
The result tab shows the network in its full size. If you are satisfied with the results, hit the Done button and the R code to produce the plot is automatically inserted in your script. Or you can directly save the result as a png file.
