1.1 What is a Network?

These days, networks and talk about “social networks” is everywhere. It was not always so, the discipline of social network analysis (SNA) developed quietly during the 1960s and 1970s out of scattered lines of work in anthropology, sociology, psychology, mathematics, and communication. It wasn’t until the 1970s that a formal group was founded to study social networks (the International Network of Social Network Analysis [INSNA]). Today, network science is an interdisciplinary field uniting physics, computer science, biology, brain science, sociology, anthropology, economics, and a variety of other fields. All are come together around the idea of a “network.”

So what is a network? Minimally, a network is composed of a set of units or entities. These are some times called nodes or vertices, however what makes these units into a network is the fact that at least some pairs of them are joined by a set of links or ties. These are also sometimes called edges. So a network is essentially a set of nodes some of which are linked together. In social networks, the nodes can be people and the connections can be any type of social tie (e.g., friendship, enmity, co-working), whether positive or negative, between those people. We will discuss the different types of ties that can exist in social networks in Chapter ?? as well as the major social network theories that have been developed by sociologists, anthropologists, and organization theorists to explain why these types of ties exist, how they work, and what benefits (or drawbacks) they have for people and organizations in chapters 6 and 7.

In a point and line plot such as the one shown in figure 0.1 networks are some times shown as pictures. The convention here is that the nodes (e.g., people) are pictured as circles (or some other polygon such as a triangles or squares) and the connections between people are picture as lines or sometimes arrows. This way of representing networks is some times called a “graph”, although we will see that the idea of a graph is a little more abstract than just a picture. In Chapters ?? and ?? we will get into more details about pictorial (and non-pictorial) ways of thinking about networks and how they connect to other ways of representing them.

Given this very broad definition, it should start to dawn on you why people think that networks are everywhere. Any system of interacting parts or entities can be depicted and analyzed as a network. That is why the idea of a network cuts across the human (e.g., networks of words in a text), social (networks of students in a school), physical (networks of computers in the internet) and biological (networks of neurons in the brain) sciences. Figure 0.2 gives you an idea of the different types of networked systems that exist in the world.