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2 articles matched your search for the keywords:
Risk Behavior in Adolescence, Dynamic Systems, Friendship Formation, Peer Homogeneity, Behavioral Change

Using an Agent-Based Model to Simulate the Development of Risk Behaviors During Adolescence

Nils Schuhmacher, Laura Ballato and Paul van Geert
Journal of Artificial Societies and Social Simulation 17 (3) 1

Kyeywords: Risk Behavior in Adolescence, Dynamic Systems, Friendship Formation, Peer Homogeneity, Behavioral Change
Abstract: Adolescents tend to adopt behaviors that are similar to those of their friends, and also tend to become friends with peers that have similar interests and behaviors. This tendency towards homogeneity applies not only to conventional behaviors such as working for school and participating in sports activities, but also to risk behaviors such as drug use, oppositional behavior or unsafe sex. The current study aims at building an agent model to answer the following related questions: how do friendship groups evolve and what is the role of behavioral similarity in friendship formation? How does homogeneity among peers emerge, with regard to conventional as well as risk behaviors? On the basis of the theoretical and empirical literature on friendship selection and influences on risk behavior during adolescence we first developed a conceptual framework, which was then translated into a mathematical model of a dynamic system and implemented as an agent-based computer simulation consisting of simple behavioral rules and principles. Each agent in the model holds distinct property matrices including an individual behavioral profile with a list of risky (i.e., alcohol use, aggressiveness, soft drugs) and conventional behaviors (i.e., school attendance, sports, work). The computer model simulates the development, during one school year, of a social network (i.e., formation of friendships and cliques), the (dyadic) interactions between pupils and their behavioral profiles. During the course of simulation, the agents’ behavioral profiles change on the basis of their interactions resulting in individual developmental curves of conventional and risk behaviors. These profiles are used to calculate the (behavioral) similarity and differences between the various agents. Generally, the model output is analyzed by means of visual inspection (i.e., plotting developmental curves of behavior and social networks), systematic comparison and by calculating additional measures (i.e., using specific social analysis software packages). Simulation results conclusively indicate model validity. The model simulates qualitative properties currently found in research on adolescent development, namely the role of homophily, the appearance of friendship clusters, and the increase in behavioral homogeneity among friends. The model not only converges with empirical findings, but furthermore helps to explain social psychological phenomena (e.g., the emergence of homophily among adolescents).

Learning Opinions by Observing Actions: Simulation of Opinion Dynamics Using an Action-Opinion Inference Model

Tanzhe Tang and Caspar G. Chorus
Journal of Artificial Societies and Social Simulation 22 (3) 2

Kyeywords: Opinion Dynamics, Norm Formation, Voter Model, Behavioral Change
Abstract: Opinion dynamics models are based on the implicit assumption that people can observe the opinions of others directly, and update their own opinions based on the observation. This assumption significantly reduces the complexity of the process of learning opinions, but seems to be rather unrealistic. Instead, we argue that the opinion itself is unobservable, and that people attempt to infer the opinions of others by observing and interpreting their actions. Building on the notion of Bayesian learning, we introduce an action-opinion inference model (AOI model); this model describes and predicts opinion dynamics where actions are governed by underlying opinions, and each agent changes her opinion according to her inference of others’ opinions from their actions. We study different action-opinion relations in the framework of the AOI model, and show how opinion dynamics are determined by the relations between opinions and actions. We also show that the well-known voter model can be formulated as being a special case of the AOI model when adopting a bijective action-opinion relation. Furthermore, we show that a so-called inclusive opinion, which is congruent with more than one action (in contrast with an exclusive opinion which is only congruent with one action), plays a special role in the dynamic process of opinion spreading. Specifically, the system containing an inclusive opinion always ends up with a full consensus of an exclusive opinion that is incompatible with the inclusive opinion, or with a mixed state of other opinions, including the inclusive opinion itself. A mathematical solution is given for some simple action-opinion relations to help better understand and interpret the simulation results. Finally, the AOI model is compared with the constrained voter model and the language competition model; several avenues for further research are discussed at the end of the paper.