the basics of network computing

MICHAEL T. HEANEY

UNIVERSITY OF MICHIGANAUGUST 31 , 20113-HOUR LESSON

The Basics of Network Computing

Plan for the Afternoon

Choosing a Network ProgramWorking with Network DataBasic network statisticsVisualization

Principal Tasks of Network Computing

Visualization of Networks

Calculation of Descriptive Statistics

Advanced Network Analysis (e.g., ERGM)

When considering which statistical package to use, consider which of the above tasks your work will focus on.

UCINet

Operates well in the familiar windows environment, but may be difficult to use with Apple computers.

Allows calculation of most standard network statistics, but is less adept at handling advanced analysis (e.g., ERGM).

Point-and-click approach is relatively easy to learn, but it can be a bit clunky.

Available here: http://www.analytictech.com/ucinet/download.htm

Statnet in R

Operates well in both Windows and Apple computing environments

Performs both basic and advanced network analyses

Users can develop own network analysis routines

Steep learning curve

Available here: http://statnetproject.org/

Some Other Packages

MelNet – Specializes in Exponential Random Graph Models. Available: http://www.sna.unimelb.edu.au/

Pajek – Specializes in large network analysis. Available: http://vlado.fmf.uni-lj.si/pub/networks/pajek/

SoNIA – Visualizing Dynamic Networks. Available: http://www.stanford.edu/group/sonia/

And more…..

UCINet

A good place to start training even if you are going to shift to another program.

Importing Data

Simplest approach is to read an Excel file.

1. Open UCINet2. Click on Spreadsheet Icon3. File Open Excel Files Filename.xlsx4. In this case, open Hrmatrix.xlsx5. Save as UCINET 7 dataset6. Note the creation of two files filename.##h

and filename. ##d – you will need both of these files in order to use UCINET data.

Data List Files

A good alternative when you are working with large data sets

Create using a simple text file:

dl nr = 1945 nc = 525, format = edgelist2,labels embeddeddata:10270716051 Communist10270716049 UFPJ10270716048 BrooklynPeace10270716045 BrooklynPeace10270716045 UFPJ

Read a Data List File

Data Import Text File DL… Contact_Network_Data OK

More Varied DL Formats for Data

Best to learn this on your own using UCINet help

Help Help Topics DL

Basic Data Analysis – Density

Network Cohesion (new) Density Overall Hrmatrix

Compute Density with Two-Mode Data

Network 2-Mode networks 2-mode Cohesion Input 2-mode incidence matrix OK

Basic Network Analysis – Centrality

Network Centrality and Power Multiple Measures (old)

Using Your Centrality Data in Statistical Analysis

Spreadsheet File Open CentralitySave as type ExcelExcel File Open

Compute Centrality with Two-Mode Data

Network 2-Mode Networks 2-Mode Centrality Input 2-mode matrix Contact_Network_Data.##h OK

Convert Two-Mode Data to One-Mode Data

Data Affiliations (2-mode to 1-mode) Input data … Contact_Network_Data Which mode Column [for this particular example]

Using Your Affiliation Data

Note that your new one-mode data (i.e., affiliation data) has been saved as a new file: Contact_Network_Data-ColAff

You can conduct all network analysis on this dataset

Let’s look at it:Spreadsheet File Open

Contact_Network_Data-ColAff OKNote that your cells make are counts of

affiliations, which is why we call this affiliation data

Dichotomizing Data

Are data may be valued, but we may preferred that they be dichotomous

Transform Dichotomize Contact_Network_Data-ColAff

Our output will now have only 1s and 0s

Basic Visualization

Visualize NetdrawFile Open Ucinet Dataset Network

Choose File

Refine Visualization

Open Ucinet dataset Attribute data HRattributes

Properties Lines Arrow Heads Visible Off

Properties Nodes Symbols Size Attribute Based Age

Properties Nodes Symbols Shape Attribute Based English_language

Layout Graph-Theoretic Layout Spring Embedding OK

A New View of the Network

Visualizing Contact Network Data

UCINet Spreadsheet File Open Excel Files Hybrid_Variable.xlsx

File Save As UCINet 7 dataset Hybrid_Variable

Visualize NetdrawFile Open Ucinet Dataset Network

Contact_Network_Data-ColAff File Open Ucinet Dataset Attribute data Hybrid_Variable

Visualizing Contact Network Data – Continued

Click on delete isolates buttonsLayout Graph Theoretic Layout Spring

Embedding (You may need to do this twice)Analysis Components OK

Visualizing Contact Network Data – Continued

Click on MC button to look at main component only

Turn off labels, arrow headsRepeat spring embeddingProperties Lines Size Tie Strength 1

to 10Properties Nodes Symbols Shape

Attribute Based Select Attribute Hybrid Variable OK

Click a node Choose label visible

Visualizing Contact Network Data – Continued

Analysis Subgroups Factions 2 (or 3 or 4) Go!

Next Steps

Multiplex VisualizationsThree Dimensional VisualizationsAdvanced analysis Exponential Random

Graph Models