A general understanding of the concept of social networks has emerged over the last decade, primarily as a result of the popularity of social media sites such as Facebook, Twitter, and LinkedIn. However, both the mobilization of social networks to accomplish goals and the study of the structure and function of these social arrangements has been carried out for much longer than the relatively recent, and very rapid, uptake of enabling information and communication technologies would seem to imply. Social network analysis (SNA) is proving to be a powerful tool for understanding collective action. It has its origins in the sociological study of small groups and interpersonal relationships, especially as outlined in the works of Georg Simmel (1858-1918), and in the representational and analytical techniques developed in the branch of mathematics known as graph theory.
The two fundamental concepts at the core of SNA are nodes and links. Nodes are the discrete social objects that make up the network, such as individuals, communities, organizations, or countries. Links, or ties, identify and describe the relationships between nodes, and they can differ in at least four ways.
The quality of a tie refers to the substantive nature of the relationship between nodes, whether it be friendship, romance, working together, or belonging to the same voluntary association. The quantity of a tie refers to the relative strength of the relationship it represents. For example, we consider some of our friends to be better or closer than others, perhaps on the basis of a deeper emotional bond, or some shared experience. Multiplexity represents the idea that the relationship between nodes may be based on more than one quality. So, for instance, you may be in a romantic relationship with someone you work with. Thus, the tie between the two of you would have a multiplexity of two. Symmetry refers to the amount of reciprocity between nodes, with respect to a particular tie. So, if one of your friends assesses the strength of your friendship the same way that you do, then this relationship is highly symmetrical. However, if a friend or family member relies on you for moral support to a greater extent than you rely on them, then this is not a symmetrical relationship.
Social networks can also differ with respect to size and scale. The number of nodes may be limited to the members of an immediate or extended family, or it may expand upwards to the hundreds of thousands of followers that some celebrities have on Facebook. These fan-based linkages can be extremely non-symmetrical, as in the case of fake news icon Stephen Colbert, who has more than four million followers on Twitter, and yet he follows no one. Network size tends to illustrate the phenomenon known as cumulative advantage, or what mathematicians refer to as a power law. What this means is that, as the number of your connections increases, you are likely to observe a very dramatic rise in the number of connections, as if your initial set of connections were off establishing connections of their own.
The scale of a network is a measure of how distributed the network is geographically, whether it be confined to a neighborhood, for example, or covering a region, nation, or the world. Sticking with celebrities for a moment, authors like Paolo Coelho and Orhan Pamuk, whose novels have sold millions of copies in multiple languages, attract a large number of followers on social media sites from all over the globe. In this way, individuals who would otherwise never likely even know of each others’ existence are provided with the potential to interact through the node that represents their common interest in contemporary literature.
Moving away from social media and the sorts of highly non-symmetrical networks associated with celebrities, in 1973, Stanford University sociologist Mark Granovetter published an article called “The strength of weak ties.” In this highly cited work, the author clearly demonstrates the potential for SNA when he is able to show that acquaintances are actually more important than close friends when it comes to searching for a job.
The next article in the series will take a closer look at some characteristics of network connections.