Home | Intro to SNA

Intro to SNA

This section of the site covers the principal achievements of SNA as packaged in the UCINET software. We start with techniques for collecting and organizing network data and creating network diagrams. We then look at SNA’s measures of network cohesion and node centrality before moving to its ways of understanding the topography of networks.

The NetDraw/UCINET interface – Taster

Preliminaries: Setting up Windows Explorer In Explorer window, View tab, ‘Panes’ to Navigation Pane, check ‘Expand to open folder’. In the Layout panel choose the Details view and in the Show/Hide panel check ‘File name extensions’. These settings allow you to track your folders and files and know what programs they are associated with (Notepad = .txt; Excel = .xlsx; ...

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Di-ties: The building blocks of social network research

Social ties: the basic units of information and observation for empirical network research Social network research deals with social ties, actual and perceived, between two actual people. An individual has many social ties of different sorts (parent, co-worker, friend etc.). We identify a social tie by naming the connected two people and the type of social tie, or ties, they ...

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Datasets are like storage jars

SNA datasets in UCINET and NetDraw

SNA datasets (as opposed to ‘data’) comprise collections of separate files that mesh together through direct, text-based linkages. They are, basically, relational databases. For SNA a ‘network’ is a set of ties for a single, defined relation. Thus, for example, the Krack-Sociom example contains three defined relations (Advice, Friendship and Reports To) and may be spoken of as three (social) ...

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MyNames: Collecting egonet, network data (section one)

This exercise simply invites you to compile your own egonet dataset to familiarize yourself with the mechanics of handling network data. It uses the basic egonet data collection of a name generator and follow-up questions to create a dataset we label MyNames. Using your own egonet data allows you to connect social network research methods to a real world setting. ...

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MyNames: Collecting egonet, network data (section two)

This section assumes you have your MyNames data organised into VNA format. For good housekeeping [see … above] check that you have a Windows folder labelled MyNames (or similar) and it is the UCINET default folder. Task One: Read the (VNA) tie data into UCINET (DL Editor ->Edgearray1) There are multiple ways to enter tie data into UCINET. NetDraw can ...

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Suggests a 1.5 ego-centric network (egonet)

Collecting and analysing 1.5 egonet data: MyPersComm

Structural analyses of egonets are only interesting if we have 1.5 (alter-alter) data. We can apply the same procedures to these 1.5 egonets that we use with whole networks tomorrow. Ron Burt (Structural Holes 1992) developed a significant array of structural measures specific to 1.5 egonets. These are available in UCINET. We need to collect your alter-alter data and map ...

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Krack-Sociom dataset

This dataset was compiled with a sociometric survey of 21 executives working in a hi-tech (for the time) startup. Respondents were give a full roster of (21) names and asked to nominate who they went to for advice (Advice relation), and who they considered a friend (Friendship relation). We also know who each respondent reported to (Report relation). The dataset ...

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Whole networks – Density

Random graphs The top-down WN-SNA perspective on network data has generated a lot of work with random graph modelling. This modelling uses computer simulations to explore ideas about the emergence of networks. For mathematicians, graphs are abstract models of network data, they are constructed entities defined as a set of nodes and specifications of di-ties between pairs; the basic SNA ...

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Globe and geodesics

Paths and Geodesic distances

Network software can trace all the paths that connect any two nodes. There are many possible paths. SNA focuses on the shortest paths which it calls ‘geodesic paths’ or simply ‘geodesics’. (A geodesic is the shortest path on a curved surface. Thus the geodesic paths on a conventional atlas – Mercator projection – will appear as arcs.) What is a ...

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Node centrality: Degree based measures

I think of (node) centrality measures as giving an ‘inside-out’ perspective on the network within which the node is embedded. Calling it centrality implies a ‘top-down’ perspective and a centralized organization of network diagrams. Remember that the layout algorithm for network diagrams worked by bringing the most connected nodes to the centre. We see this with the operation of Netdraw’s ...

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