Tore Opsahl

Import and Export Functions

Networks can be imported and exported into tnet from a range of other network analysis programmes. This page refers to weighted one-mode networks as most programmes cannot deal with two-mode and longitudinal networks.

UCINET

UCINET is a Windows software for general analysis of social network data (UCINET’s website). This programme is not free, but there is a 30-day trial period.

Import into tnet

Weighted one-mode networks in UCINET can be analysed in tnet by following these steps. First, go to UCINET, and select Data > Export > Raw …

• Input dataset: <your dataset>
• Output format: Edgelist1
• (edgelist only) Type: directed
• Minimum tie val allowed: 1
• Embed row labels: NO
• Embed column labels: NO
• Output dataset: c:\data_to_tnet.txt
  (this can be changed, but then you need to changed the entries further down in this example)

Second, an exclamation mark at the end of the outputted file must be manually removed. UCINET adds an exclamation mark at the end of each file, and this cannot be read by R/tnet in a simple way. One way of doing this, is to open c:\data_to_tnet in Notepad, and delete the last line (this should just be !).

Third, the file can be loaded in R as an object called net by typing the following command (note that the \ has become /):

data <- read.table(file="c:/data_to_tnet.txt")

Export from tnet

There is a specific function in tnet for exporting networks to UCINET. This function is called tnet_ucinet. This function works by taking three parameters:

• net: This should be the network to export
• type: Which type of network this is (default is to auto-detect, see as.tnet)
• file: The desired file name of the network (default is to create a file in the working directory with the current time, for example, tnet_ucinet_network-2011-04-10_150817.dl).

The file can then be loaded in UCINET by using the DL import function. You can find this function through the menu: Data > Import > DL. When the function’s dialog box opens, you must select the downloaded file containing the dataset by clicking on “…” after “Input text file in DL format”. The second box can be set to the default, but do remember, and change if you wish, the name that appears in the third box as this will be the name of the internal UCINET file.

The R-package igraph

igraph is a free software package for creating and manipulating undirected and directed graphs. This package has been implemented in R, and tnet depends on it for various heavy calculations.

Import into tnet

As both igraph and tnet are implemented in R, data can easily be transferred between the two packages. The following code shows how to extract the edgelist from igraph, and use it in tnet.

# Load igraph and tnet
library(tnet)

# Create a sample igraph network with tie weights
g <- erdos.renyi.game(6, 0.4, type="gnp")
E(g)$weight <- sample(1:4, size=ecount(g), replace=TRUE)

# Extract edgelist and a 1 to the node id's as igraph starts from 0 while tnet 1.
net <- cbind(get.edgelist(g, names=FALSE), E(g)$weight)

# For binary networks, a third column of 1s must be added
if(ncol(net)==2)
  net <- cbind(net, 1)

# For undirected networks, the symmetrise function must be run
if(!is.directed(g))
  net <- symmetrise_w(net)

# Ensure that it conforms to the tnet standard
net <- as.tnet(net, type="weighted one-mode tnet")

Export from tnet

There is a special function in tnet for exporting networks to igraph (tnet_igraph). Below is an example of how it can be used.

# Load igraph and tnet
library(tnet)

# Create a sample tnet network
net <- rg_w(nodes=10, arcs=0.4, weights=1:4, directed=FALSE)

# Create igraph object
g <- tnet_igraph(net,type="weighted one-mode tnet")

# Get summary statistics
summary(g)

Pajek

Pajek is a Windows programme for analysis and visualization of large networks.

Import into tnet

To export your data from Pajek to tnet, you must first save the network in a Pajek .net file, you can do this by going to File > Network > Save, and selecting a location. In this example, I will use c:\data_to_tnet.net. Then you need to open the .net file, e.g. c:\data_to_tnet.net in Notepad as shown on picture to the right. You need to delete the lines from “*Vertices” to, and including, “*Arcs”, so that all you have left is three columns with numbers. Then save the file.

Then, you can open R, and type (note that the \ has become /):

data <- read.table(file="c:/data_to_tnet.net")

The R-package sna

The sna R-package is a collection of routines for social network analysis. It has been developed by Carter Butts at University of California, Irvine.

Import into tnet

To import an sna-object into tnet, you must use the as.edgelist.sna-function.

# Load sna and tnet
library(sna)
library(tnet)

# Create a sample sna network
g <- rgraph(n=10, tprob=0.4, mode="graph")

# Extract edgelist
net <- as.edgelist.sna(g)

# Ensure that it conforms to the tnet standard
net <- as.tnet(net, type="weighted one-mode tnet")

Export from tnet

To load a network into sna, a matrix must be created. This can be done using the following code:

# Load sna and tnet
library(sna)
library(tnet)

# Create a sample tnet network
net <- rg_w(nodes=6, arcs=0.4, weights=1:4, directed=FALSE)

# Create sna object
net <- as.matrix(net)
N <- max(c(net[,"i"],net[,"j"]))
g <- matrix(data=0, nrow=N, ncol=N)
g[net[,c("i","j")]] <- net[,"w"]

# Ensure that it conforms to the sna standard
g <- as.sociomatrix.sna(g)

The R-package network

The R-package network is a basic package that many other R-packages use for their data handling. As this package cannot handle weighted data, they are remove in any transfer process.

Import into tnet

To import a network-object into tnet, the network can be extracted as an edgelist using the as.matrix.net with the matrix.type-parameter set to edgelist. Below is an example.

# Load sna and tnet
library(network)
library(tnet)

# Create sample network object
g <- network.initialize(6, directed=FALSE)
g <- add.edge(g, 1, 2)
g <- add.edge(g, 1, 3)
g <- add.edge(g, 2, 4)
g <- add.edge(g, 2, 5)
g <- add.edge(g, 5, 6)

# Extract edgelist, and add a column of 1's
net <- as.matrix.network(g,matrix.type="edgelist")
net <- cbind(net, 1)

# For undirected networks, the symmetrise function must be run
if(!network::is.directed(g))
  net <- symmetrise_w(net)

# Ensure that it conforms to the tnet standard
net <- as.tnet(net, type="weighted one-mode tnet")

Export from tnet

To transfer a tnet object into the network package, …

# Load sna and tnet
library(network)
library(tnet)

# Create a sample tnet network
net <- rg_w(nodes=6, arcs=0.4, weights=1:4, directed=FALSE)

# Create sna object
net <- as.matrix(net)
N <- max(c(net[,"i"],net[,"j"]))
g <- matrix(data=0, nrow=N, ncol=N)
g[net[,c("i","j")]] <- net[,"w"]
g <- network(g, directed=FALSE)