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The term social network refers to a social structure made up of interconnected actors. These actors can be individuals, groups, cities, organizations, or even online communities. Social network research is the study of the relationships and network positions between social actors in identifiable social structures. Since the early 1980s, the application of social network methods has grown exponentially. This increased interest has led to sophistication in both the design and analysis of social network research. This entry focuses on the design aspect—that is, the composition of networks. It describes three critical components of social network research—nodes, ties, and boundaries—and outlines recommendations for improving the validity of inferences drawn from this research.

Components of Social Networks

Social network research generally focuses on understanding one or a combination of three components of a social network: nodes, ties, and boundaries. These components provide social network scholars with the foundations for digesting existing research and designing their own social network studies.

Nodes

In social network research, nodes are the actors (e.g., individuals, groups, firms) within a network. A node can either be an individual actor or a collective of actors, depending on the study’s analysis level. For microlevel studies, nodes are the individual actors in the network. In Figure 1a, the three nodes are individual doctoral students within a cohort. For macrolevel research, nodes are often defined as collectives of actors, such as groups or organizations. Figure 1b shows three collectives of actors (e.g., students) connected as nodes in a macro network (e.g., schools). For meso-level research, nodes combine the characteristics of nodes at micro- and macrolevels. For instance, board directors of one firm connect their organizations to others through shared board membership.

Ties

Network ties refer to the relationships between nodes in a social network. Two broad classifications of ties have been identified in the literature: relational states and relational events. Relational states can further be classified into either similarities or social relations. Similarities occur when two actors share attributes such as demographic characteristics, attitudes, locations, or group membership. Social relations are ties based on the nature of interpersonal relationships between two actors. In social network research, scholars have examined three types of social relations: roles, affect, and cognition. Role ties (e.g., friendship) reflect the role of an actor in a relationship. Affective ties (e.g., dislike) are based on social actors’ feelings about one another. Finally, cognitive ties (e.g., trust) are based on the cognitive awareness of actors. Relational events are also classified into two categories: interactions and flows. Interactions are observable behaviors directed toward other actors (e.g., advice-giving). Flows refer to the resources and outcomes of interactions (e.g., knowledge).

Figure 1 Micro- and Macrolevel Networks

Boundaries

Network boundaries reflect the structure of the network, specifying what nodes are included in a network. Network boundaries can be specified based on a combination of three rules: positions, events, and relations. Using a position rule requires researchers to define nodes based on formally defined roles in the social system (e.g., a network of doctoral students in a business school). An event-based rule involves defining the boundaries of the network by the presence of actors at a particular event (e.g., doctoral students who attended a doctoral student consortium at a conference). Finally, a relation-based rule involves defining boundaries based on specific shared relationships. This approach typically begins with the specification of a small set of seed nodes and then expands to include others who share a specific relationship with the seed nodes (e.g., firms’ cofounders and their previous cofounders).

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