If ego network designs represent one pole of potential research designs for gathering social network data, the opposite end is represented by complete network strategies.40 In complete network designs, the idea is to enumerate first a population of interest, and second all of the relationships between members of that population. There are a variety of strategies for defining who is (and is not) a member of that focal population. Moreover, for a complete network design to be meaningfully thought of has having demarcated the full population of interest, it’s helpful for the researcher to be interested in studying a population with an easily identifiable boundary (see more about this in the section on “boundary specification” below).
The differences between complete and ego network designs often have substantial implications for what can be theoretically and empirically addressed. That is, what is known in the networks literature as “indirect influence” —i.e., a node being influenced by another that they are not directly connected to (or are connected to by a distance of two or more)—is not estimable from ego network data, but is a common question in complete network studies of interpersonal influence. In addition to these differences that shape the conceptual aims of the research, some of the practical considerations raised above for how to conduct the research differ as well. For example, a roster-based name generator is likely to be much more feasible in a complete network design than an ego network study; simply, the researcher is more likely to have an enumerable list of the population members in the complete network case.