You’re beginning a new research project that has a relational focus, and therefore need to collect some social network data. You’ve been studying insurance companies for years, suggesting they mimic one another’s policies, but haven’t had the data needed to show what determines which organizations adopt strategies from which others, and which strike out on their own. Or perhaps you’re an epidemiologist who wants to trace the spread of a new Ebola outbreak through a population, in hopes to curtail how many people are infected in this—and future—outbreaks. Or maybe you’re consulting on a political campaign, trying to determine more accurately which of our friends and family members most strongly influence our own voting behaviors; with that information, maybe you want to design targeted advertising that optimizes how to leverage these patterns as your campaign comes closer to election day.
Each of these questions has a relational aspect to it. That means to answer these types of questions precisely and accurately, you need data linking the individual people (or organizations) to one another. How would you go about gathering those data?
In virtually any social science discipline, new grad students are shuttled through a research design course basically as soon as they arrive. So, I also make the assumption that most social scientists have basic training in general research methods.3 With those tools in hand, it may seem plausible that gathering network data is not really any different than what’s been required to gather details on an individual’s age, gender, educational background, or behavioral profile. Or, if organizations are your focus, and you’ve been examining their internal leadership characteristics and institutional histories, it may seem that turning your attention to how these organizations are linked to one another simply requires asking a few more questions beyond those you typically include.
But, as we’ll see in the chapters that follow, studying networks requires more than simply adding some relationship variables to an already extensive set of individual-level characteristics. In fact, some have argued that studying social networks requires altering the paradigm of social science altogether (Wellman 1988). Instead of focusing on the patterns across the characteristics of members within a population (whether individuals or organizations), social network scholars aim to understand the patterns among the relationships between those members.4
In the remainder of this chapter, I outline some of the conceptual and theoretical ways that network research differs from the more familiar general social scientific approaches. This discussion of how network research “thinks” differently, in turn, sets up the corresponding methodological approaches that I describe in the chapters that follow.
As you read, it will likely be the case for most readers that only a subset of the ideas here will apply to the types of questions you have in mind. As such, you shouldn’t feel obligated to read for comprehensive understanding of the whole chapter, but instead selectively seek out the types of questions you see as fitting your own work. Regardless of the type(s) of questions you identify as your own, each of the alternatives described will have direct ramifications for the methodological considerations in the chapters that follow.