Beyond Networks in Structural Theories of Exchange: Promises from Computational Social Science

The research community currently employs four very different versions of the social network concept: A social network is seen as a set of socially constructed role relations (e.g., friends, business partners), a set of interpersonal sentiments (e.g., liking, trust), a pattern of behavioral social interaction (e.g., conversations, citations), or an opportunity structure for exchange. Researchers conventionally assume these conceptualizations are interchangeable as social ties, and some employ composite measures that aim to capture more than one dimension. Even so, important discrepancies often appear for non-ties (as dyads where a specific role relation or sentiment is not reported, a specific form of interaction is not observed, or exchange is not possible).

Investigating the interplay across the four definitions is a step toward developing scope conditions for generalization and application of theory across these domains.

This step is timely because emerging tools of computational social science – wearable sensors, logs of telecommunication, online exchange, or other interaction – now allow us to observe the fine-grained dynamics of interaction over time. Combined with cutting-edge methods for analysis, these lenses allow us to move beyond reified notions of social ties (and non-ties) and instead directly observe and analyze the dynamic and structural interdependencies of social interaction behavior.

This unprecedented opportunity invites us to refashion dynamic structural theories of exchange that advance “beyond networks” to unify previously disjoint research streams on relationships, interaction, and opportunity structures.