One of the great lessons from the last half century of research on social networks is that relationships are constantly in flux. While much social network analysis focuses on static relationships between actors, there is also a rich tradition of work extending back to foundational studies in network science focused on the notion that network change is an indelible aspect of social life for human and non-human actors alike (e.g., Bott, 1957; Heider, 1946; Newcomb 1961; Rapoport, 1949; Sampson, 1969). Today, social network researchers benefit from this history in that a host of methods to collect and analyze such dynamic network data have been developed. Among them, the methods based on stochastic process theory have given rise to a paradigm where inferences and predictions can be made on the mechanisms that drive changes in social structure.
Boats and Tides and "Trickle Down" Theories: What Economists Presume about Wellbeing When They Employ Stochastic Process Theory in Modeling Behavior
