- visualization of networks: what for? how?
- visualization parameters
- best practices — esthetics and productivity
- data formats and preparation
- the description of data sets which are used in examples
- the beginning of work with igraph
In the second part: colors and fonts in diagrams R.
In the third part: parameters of graphs, tops and edges.
In the fourth part: placements of network.
In this part: emphasis of properties of network, tops, edges, ways.
Emphasis of properties of network
Pay attention that our diagram of network is still not too useful. We can define type and the size of tops, but we can tell the little about structure as the studied edges are very close located. One of ways to solve problem — to look, whether it is possible "to thin out" network, having left only the most significant communications and having discarded the others.
hist(links$weight) mean(links$weight) sd(links$weight)
There are also more difficult ways to select key edges, but in this example we will leave only those which weight exceeds mean value for network. In igraph it is possible to delete edges with the help
cut.off <- mean(links$weight) net.sp <- delete.edges(net, E(net)[weight<cut.off]) l <- layout.fruchterman.reingold(net.sp, repulserad=vcount(net)^2.1) plot(net.sp, layout=l)
Other approach to solution — to display two relationship types (links and references) separately:
E(net)$width <- 1.5 plot(net, edge.color=c("dark red", "slategrey")[(E(net)$type=="hyperlink")+1], vertex.color="gray40", layout=layout.circle)
net.m <- net - E(net)[E(net)$type=="hyperlink"] # другой способ удалить ребра net.h <- net - E(net)[E(net)$type=="mention"] par(mfrow=c(1,2)) plot(net.h, vertex.color="orange", main="Tie: Hyperlink") # Связь: ссылка plot(net.m, vertex.color="lightsteelblue2", main="Tie: Mention") # Связь: упоминание
l <- layout.fruchterman.reingold(net) plot(net.h, vertex.color="orange", layout=l, main="Tie: Hyperlink") plot(net.m, vertex.color="lightsteelblue2", layout=l, main="Tie: Mention")
It is possible also to try to make the card of network more useful, having shown associations in it:
V(net)$community <- optimal.community(net)$membership colrs <- adjustcolor( c("gray50", "tomato", "gold", "yellowgreen"), alpha=.6) plot(net, vertex.color=colrs[V(net)$community])
Emphasis of some tops or edges
Sometimes it is necessary to focus visualization at certain top or group of tops. In our example of network of mass media it is possible to investigate distribution of information between central objects. For example, let's display distance from NYT (New York Times). Function
shortest.paths(as the title indicates) returns matrix of the shortest ways between tops to networks.
dist.from.NYT <- shortest.paths(net, algorithm="unweighted")[1,] oranges <- colorRampPalette(c("dark red", "gold")) col <- oranges(max(dist.from.NYT)+1)[dist.from.NYT+1] plot(net, vertex.color=col, vertex.label=dist.from.NYT, edge.arrow.size=.6, vertex.label.color="white")
Or it is possible to show all next neighbors of WSJ (Wall Street Journal). Pay attention that function
neighborsfinds all tops in a single step from central object. Similar function which finds all edges for node, is called
col <- rep("grey40", vcount(net)) col[V(net)$media=="Wall Street Journal"] <- "#ff5100" neigh.nodes <- neighbors(net, V(net)[media=="Wall Street Journal"], mode="out") col[neigh.nodes] <- "#ff9d00" plot(net, vertex.color=col)
Other way to draw attention to group of tops — "to mark" them:
plot(net, mark.groups=c(1,4,5,8), mark.col="#C5E5E7", mark.border=NA)
# Пометить несколько групп: plot(net, mark.groups=list(c(1,4,5,8), c(15:17)), mark.col=c("#C5E5E7","#ECD89A"), mark.border=NA)
It is also possible to select way to networks:
news.path <- get.shortest.paths(net, V(net)[media=="MSNBC"], V(net)[media=="New York Post"], mode="all", output="both") # Создать переменную цвета ребер: ecol <- rep("gray80", ecount(net)) ecol[unlist(news.path$epath)] <- "orange" # Создать переменную ширины ребер: ew <- rep(2, ecount(net)) ew[unlist(news.path$epath)] <- 4 # Создать переменную цвета вершин: vcol <- rep("gray40", vcount(net)) vcol[unlist(news.path$vpath)] <- "gold" plot(net, vertex.color=vcol, edge.color=ecol, edge.width=ew, edge.arrow.mode=0)
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