Dolphin Social Network

1. R Markdown

This is an R Markdown document. Markdown is a simple formatting syntax for authoring HTML, PDF, and MS Word documents. For more details on using R Markdown see http://rmarkdown.rstudio.com.

When you click the Knit button a document will be generated that includes both content as well as the output of any embedded R code chunks within the document.

2. Programming Assignment

Find some network data that you think is suitable and that you would like to visualize. Here are some sites that provide links to a wide variety of different graph/network datasets:

Stanford Large Network Dataset Collection
UCI Network Data Repository

Choose a visualization platform and parse the data into a format suitable for the tools you will use.

3. Environment Setup

This analysis requires to load the following R pacakages : iGraph,dplyr,networkD3

suppressMessages(library('igraph'))

## Warning: package 'igraph' was built under R version 3.5.3

suppressMessages(library('dplyr'))

## Warning: package 'dplyr' was built under R version 3.5.2

suppressMessages(library('networkD3'))

## Warning: package 'networkD3' was built under R version 3.5.3

3. Data Collection

This particular assignment exhibits the undirected social network between 62 different Dolphine species living off in a community in New Zealand. The whole dataset has been complied by the followings:

D. Lusseau, K. Schneider, O. J. Boisseau, P. Haase, E. Slooten, and S. M. Dawson, The bottlenose dolphin community of Doubtful Sound features a large proportion of long-lasting associations, Behavioral Ecology and Sociobiology 54, 396-405 (2003).

For data collection purpose, R code loaded the whole dataset found here : https://networkdata.ics.uci.edu/data/dolphins/dolphins.gml

dolphins <- read.graph(file='https://networkdata.ics.uci.edu/data/dolphins/dolphins.gml', format='gml')

4. Data Manipulation

During this step the centrality measure has been calculated by the function “betweenness” and “closeness”.

NetworkD3 package edge references to nodes start from 0 so the edge value has been adjusted here

dolphins_nodes <- get.data.frame(dolphins, what = 'vertices') %>% mutate(Betweenness = betweenness(dolphins), Closeness = closeness(dolphins))
dolphins_edges <- get.data.frame(dolphins, what = 'edges')

dolphins_edges$from <- dolphins_edges$from - 1
dolphins_edges$to <- dolphins_edges$to - 1

5. Data Visualization

Create an interactive network D3 graph to achieve the following purpose :

• click-and-drag the nodes.
• double click on any node for zooming.
• move your cursor to the graph and scroll can zoom on whole graph.
• see the social network among all the dolphin species.

forceNetwork(Links = dolphins_edges, Nodes = dolphins_nodes,
             Source = "from", Target ="to",
             colourScale = JS("d3.scaleOrdinal(d3.schemeCategory20);"),
             radiusCalculation = JS("Math.sqrt(d.nodesize)+6"),
             NodeID = "label",
             Nodesize = "id",
             Group = "id",
             linkDistance = 100,opacity = 1.0, zoom = TRUE,fontSize = 12,opacityNoHover = TRUE)

6. References

https://www.rdocumentation.org/packages/networkD3/versions/0.4/topics/forceNetwork

https://igraph.org/r/