What is SNA and why use it?
WHAT IS SNA?
Borgatti and Halgin (2011) give us a good definition of a network:
A network consists of a set of actors or nodes along with a set of ties of a specified type (such as friendship) that link them. The ties interconnect through shared end points to form paths that indirectly link nodes that are not directly tied. The pattern of ties in a network yields a particular structure, and nodes occupy positions within this structure. Much of the theoretical wealth of network analysis consists of characterizing network structures (e.g., small-worldness) and node positions (e.g., centrality) and relating these to group and node outcomes. (Borgatti & Halgin, 2011, p. 2)
We can consider trains lines and stations as constituting a network. However, a social network is one which involves people in some way.
Network ties can be, for example, friendship, advice, trust, knowledge transfer, trade, and even bullying. Any type of relationship can be studied using SNA. Importantly, the more precise the network tie, the great the possibility for understanding the network. For example, looking at a network of ‘trusted advisors’ is likely to be more informative than a network of ‘people you know or consider to be an acquaintance’.
Network actors can be people, organisations, groups, countries, ideas, or some combination of these. Notably, actors can have attributes – for example (in the case of people) age, gender, nationalities, political views, motivations, and personality type. For organisations, attributes could be number of employees, turnover, geographic location, function, and so on.
Why use SNA?
Social Network Analysis (SNA) allows you to understand the ‘patterns and implications’ of social ties (Wasserman & Faust, 1994, p. 3). Why do actors form network ties to others? For instance, why do people in organisation go to others for advice? Are particular people more likely to be the ‘go-to’ people? If so, which ones, and what does this say about the organisation. Alternatively, how do network ties affect network actors? For example, does my position in an advice-seeking network have implications on my individual performance? Do people in brokerage positions perform better than others? Questions that have been asked using SNA include:
Is my organisation siloed or connected?
How do you transfer knowledge across global boundaries?
What sort of social support network protects against mental health issues?
How do informal networks influence the culture of teams?
Is obesity contagious?
How do school friends influence academic performance?
What is the role of network in the recruitment of directors on boards?
What does a highly functioning innovation start-up ecosystem look like?
AREAS OF APPLICATION
SNA has been used within the disciplines of business and management, sociology, social psychology, health, innovation, education, criminology, political science and many more. SNA has been used to study formal and informal groups, organisations, communities, international trade and relations, amongst others.
Visualisation
‘A picture is worth a thousand words’ is an appropriate description for the value of network visualisations (see network below). Such visualisations give powerful information, such as whether the network is connected or not (this network is siloed)), whether ‘birds of a feather flock together’ (that is definitely the case here, different colours represent different groups of people), or whether there are key connectors or brokers who hold the network together (there are few of these in this network).
However, sometimes networks are so ‘busy’ and have so many connections that is difficult simply to ‘see’ what is going on (left). In such cases, SNA offers a range of possibilities to use quantitative network metrics and statistical analyses to better understand what is happening in the network beyond what the naked eye can see.
Courses
MelNet Social Network Research Group holds Social Network Analysis 5-Day Course: Theory, Method and Application each year at Swinburne University of Technology in Melbourne. This course shows you how to conduct social network research, moving from the fundamentals of networks to the use of cutting-edge statistical models for social networks. Register here.
ACSPRI holds two SNA related courses:
Introduction to Social Network Research and Analysis — the course covers data collection and research design, visualisation and basic analytic methods used in social network research.
Big Data Analysis for Social Scientists provides an introduction to the collection and analysis of socially-generated 'big data' using the R statistical software and Gephi network visualisation software.