如何使用igraph或tnet在R中创建二分网络

Question

I have an edgelist for a two mode network, similar to this:

person  Event
Amy     football_game
Sam     picnic
Bob     art_show

I want to perform an analysis on this in R, but seemingly everything I try fails. Converting it to a one mode network runs into memory limitations, and I can't figure out how to analyze it as bipartite in either igraph or tnet.

In igraph, bipartite.projection gives me all FALSE , on the igraph object created using

net <- graph.edgelist(myobject)

On tnet, I can't convert the igraph net to a tnet one, and when I try to use the original data frame, it refuses because of duplicates in the graph.

So answers to any of the following would be super appreciated:

1. How do I use the bipartite.mapping function?
2. How do I input an igraph object into tnet?
3. If all else fails, how I do I input a data frame with duplicate edges into tnet?

Sorry if these are basic questions, but there's very little documentation.

EDIT

Example:

edgelist <- read.table(text="Person    Event
                             Amy       football
                             Bob       picnic
                             Sam       artshow", 
                       header=TRUE)
edgelist <- as.matrix(edgelist)

## Igraph Issues
igraph <- graph.edgelist(edgelist)
typevector <- bipartite.projection(igraph) 
# gets all FALSE

edgelist2 <- get.edgelist(igraph)
typevector <- bipartite.projection(edgelist2) 
# same thing

## tnet issues
tnet <- as.tnet(edgelist) 
# gives error: "There are duplicate events in the edgelist"
tnet <- as.tnet(edgelist2)
clusterMat <- clustering_local_tm(tnet)  
# gives error: "max not meaningful for factors"

onemode <- projecting_tm(tnet, method="Newman") 
# gives error: "arguments must have same length"

Answer 1

In igraph a bipartite network is one that has a type vertex attribute. This attribute must be logical and must the TRUE for one of the node types and FALSE for the others. So to create a bipartite network from your edge list, you simply create a regular graph and then add the type vertex attribute:

edgelist <- read.table(text="Person    Event
                         Amy       football
                         Bob       picnic
                         Sam       artshow", 
                   header=TRUE)
igraph <- graph.data.frame(edgelist)

V(igraph)$type <- V(igraph)$name %in% edgelist[,1]
igraph
# IGRAPH DN-B 6 3 -- 
# + attr: name (v/c), type (v/x)

The 'B' letter tells you that this is a bipartite graph. You can create the unipartite projections of this network via:

bipartite.projection(igraph)
# $proj1
# IGRAPH UN-B 3 0 -- 
# + attr: name (v/c), type (v/x)
#
# $proj2
# IGRAPH UN-B 3 0 -- 
# + attr: name (v/c), type (v/x)

This will return a list of two graphs. If you think that the projection might be too big, you can first call the bipartite.projection.size function, this will give you the number of vertices and edges in both projections. The memory requirement for an igraph graph is (4m+2n)*8+O(1) bytes, where 'n' is the number of vertices and 'm' is the number of edges.