Interactions, Actors, and Time: Dynamic Network Actor Models for Relational Events

Abstract

Ample theoretical work on social networks is explicitly or implicitly concerned with the role of interpersonal interaction. However, empirical studies to date mostly focus on the analysis of stable relations. This article introduces Dynamic Network Actor Models (DyNAMs) for the study of directed, interpersonal interaction through time. The presented model addresses three important aspects of interpersonal interaction. First, interactions unfold in a larger social context and depend on complex structures in social systems. Second, interactions emanate from individuals and are based on personal preferences, restricted by the available interaction opportunities. Third, sequences of interactions develop dynamically, and the timing of interactions relative to one another contains useful information. We refer to these aspects as the network nature, the actor-oriented nature, and the dynamic nature of social interaction. A case study compares the DyNAM framework to the relational event model, a widely used statistical method for the study of social interaction data.

Social network-based distancing strategies to flatten the COVID-19 curve in a post-lockdown world

“…Similar to the classic SIR model 26 (in which individuals are susceptible, infectious or recovered) and its SEIR extension 27 (in which they are susceptible, exposed, infectious and then recovered), we assume that individuals can be in four different states: either susceptible to the disease, exposed (infected but not yet infectious), infectious or recovered. Infection occurs through social interactions, which are modelled in a similar fashion to the dynamic actor-oriented model 34 developed for relational events. More specifically, our model comprises the following steps:…”

“…The probability for i to pick j is defined as a multinomial choice probability 42 , follo wing the logic of previous relational event 34 and stochastic network models 32 . The intuition behind this distribution is that each potential partner in N i is assigned an objective function value, and choosing a partner is based on these values.…”

“…For the experiments using mixed strategies, the probability of partner choice p i ! j ð Þ I can depend on a vector of statistics and parameters 34 . The entropy based on a set parameter vector was used to calibrate the parameter for the homophily and triadic closure strategy as comparison cases.…”

“…Choices are determined stochastically; strategies increase the likelihood of interacting with specific alters but are not deterministic. The mathematical formulation that determines contact choice follows earlier approaches used in network evolution 32 and relational event models 33,34 . A flowchart of the model is presented in Fig.…”

The validity of RFID badges measuring face-to-face interactions

“…The small scale of the badge permits that they can, for example, be integrated in a name tag. We think that this technology holds great promise in psychology and other fields of behavioral sciences, in particular due to recent advancements in statistical methodology for the study of time-stamped interaction data (Butts, 2008; Pilny, Schecter, Poole, & Contractor, 2016; Stadtfeld & Block, 2017; Stadtfeld & Geyer-Schulz, 2011; Stadtfeld, Hollway, & Block, 2017).…”