In principle, anything that could be represented as a graph, could be considered a network, and analytically could be examined with SNA. This has often been the practice in the physical and biological sciences (Borgatti et al. 2009), and some in the social sciences have even argued that as one of the beauties of social network analysis—that regardless of the type of nodes or ties between them—the analytic principles can be applied to any network in much the same way (Wellman 1988).15 However, just because different networks can be analyzed with the same approaches doesn’t mean they should be. Different network types could lead to different applications of the same descriptive concepts; many core network ideas (e.g., centrality or communities) have multiple alternate strategies for their measurement, and it may be easiest to select between those based on differences between the types of networks being described.16
Moreover, the theoretical mechanisms that provide accounts for different explanatory expectations within networks differ substantially depending on the type of network being examined (Erikson 2013; Fuhse 2019; Valente and Pitts 2017); I elaborate a few of these in broad terms below. In either case—and as with any solid social science research—the aims of a network study (whether descriptive, explanatory, or otherwise), must carefully consider what the research aims to address in order to determine what sorts of data will allow them to best examine those questions. Here, we must consider what type(s) of ties the questions are about, how readily researchers can actually capture the types of ties required by their research questions, or whether they will be limited to some sort of proxies for the relationships of actual interest.
Borgatti et al. (2009) provide a typology of the types of relationships that are frequently the focus of social network research;17 for a summary, see Table 1.2. They differentiate between three primary types of ties: social relations, interactions, and flows.18
|Social Relations||Kinship||sister of, parent of|
|Role||friend of, mentor of, collaborator|
|Affective||respects, likes, dislikes|
|Cognitive||knows, knows of|
|Interactions||mutual||has sex with, converses with, fought|
|directed||cites, seeks advice from, helped|
|Flows||objective||diseases, trade, knowledge|
|subjective||attitudes, perceptions, information|
NOTE: This table is adapted from (Borgatti et al. 2009).
Social relations capture the various relationally-defined positions a person can occupy with respect to others; these often have strong social basis, and/or foundations in theoretical social science literature. Role theory asserts behavioral expectations upon occupants of certain roles (e.g., parents should behave in particular ways towards their children). Recognizing the relational basis of those roles allows us to identify how these expectations derive from the pattern of relationships that define the role, rather than a more essentialist notion of role expectations determined from the label itself. For example, a parent’s role is determined by the kinship ties they have to their co-parent, their children, and often even their own parents.19
In social relationship terms, the constellation of these others to whom the person is connected defines the role. Such kinship relations have been the focus of relational social scientists for decades (Bott 1957; Stack 1970; White and Jorion 1992; White 1963). In addition to kinship ties, describe other social relations that are based on other roles (e.g., friends), affective relationships (e.g., likes/dislikes), or cognitive links (e.g., knows the work of). This variety of social relationships shares a number of common features that make their measurement more readily available—they are generally relatively temporally stable ties, and each member of the relationships can generally readily identify both members’ participation in the relationship. This makes gathering relational information about such roles easily incorporated into a survey-based research design, by simply tacking such questions onto individually-oriented surveys.
Social interactions capture the joint participation by pairs of nodes in shared activities. The types of interactions that are most commonly studied are things like sent and received messages, engaging in sexual intercourse, the joint use of injecting drug equipment (e.g., needles), or other shared experiences (e.g., meals). Interactions are often more temporally fleeting than social relationships, and frequently aim to capture the behavioral nature of shared activities—as opposed to the social nature of roles.
Moreover, the interaction examples provided in Table Table 1.2 introduce the notion that social relationships can also be undirected (mutual) or directed. An undirected social relationship looks the same from the perspective of each party involved; each sibling is sibling to the other. Contrastingly, a directed relationship necessarily involves two members of differing, complementary, roles. A parent-child relationship involves two members occupying different roles. Many interactions are directed as well, involving sender and receiver roles (e.g., a speaker and a listener if the interaction is a specific speech unit within a conversation).
Often these roles or interactions can form the basis for potential flows between partners, which are the final type of ties identified by (2009). So, the needle-sharing mentioned above may lead to disease transmission, or conversations may allow knowledge to pass from one individual to another. Flows may also be the primary tie type of interest, independently of how roles or interactions shape their possibilities (e.g., in studies of financial remittances). Importantly, scholarship has shown that identifying the actual transmission of ideas through a population (e.g., diffusion of knowledge) can provide considerably different estimates than when we ask people to account for who influenced them on a particular idea (e.g., perception of information flows) (Young and Rees 2013). The objective–subjective distinction here is therefore primarily one for researchers to carefully consider in deciding which is the aim(s) for their research.
A research project’s aims often can readily identify one (or more) of these tie types as its primary conceptual focus. However, simply because that identification is conceptually possible does not mean that gathering data on that tie type in the theoretically-salient dimension is equally viable. For example, suppose, your interest is in mapping the risk-relevant network that promotes a chlamydia epidemic. The relevant network that you would want to map would include all sexual contacts (interactions) that occur between sero-discordant partners.20 Additionally, sero-discordance is not a permanent status, so to properly map that risk network, you’d need those interaction data at the level of individual acts, along with each individual’s time-specific sero-status. It is highly implausible that this level of measurement precision would be available to even the most scrutinizing researcher’s data collection efforts.
While this particular example is extreme, it reflects a common occurrence in social network data collection efforts. There is often necessarily conceptual slippage between the level at which researchers desire to gather data and the level that is accessible to them. That is, research must regularly rely on relational proxies—often that move “up” in the level of generalization (i.e, from flows towards social relations). We may only be able to measure social relationships that include sexual contact, not each sexual act when studying a chlamydia outbreak. Tie directionality can similarly require measurement proxies. For example, a researcher may only have access to one member of a reported relationship, and if they report having provided support to their partner, we must take them at their word that the other partner received that support. While careful qualifications within analytic interpretations can potentially acknowledge the limitations of such proxies, researchers have increasingly acknowledged that such slippages have implications beyond the measurement level, and have argued for thinking about different types of ties as having different theoretical—as well as methodological—implications that researchers must consider (Kitts 2014).
For the next 2 chapters, I will assume that researchers can match the conceptual aims to the methodological strategies of their studies. I will revisit some strategies for coping with these potential limitations in Chapter Chapter 5. Given the relational questions that can arise from the perspectives outlined above, the next chapter turns to how scholars can go about obtaining data to address these types of relational questions.