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8 articles matched your search for the keywords:
Group Formation, Peer Influence, Identity Control Theory, Social Norms, College Drinking

Introducing Emotions into the Computational Study of Social Norms: a First Evaluation

Alexander Staller and Paolo Petta
Journal of Artificial Societies and Social Simulation 4 (1) 2

Kyeywords: Social Norms, Appraisal Theory of Emotions ,Process Model of Emotions, Layered Agent Architecture, Simulation, JAM (BDI Agent Architecture), Micro-Macro Link, Aggression Control Case Study, Deontic Reasoning and Human Behaviour Models
Abstract: It is now generally recognised that emotions play an important functional role within both individuals and societies, thereby forming an important bond between these two levels of analysis. In particular, there is a bi-directional interrelationship between social norms and emotions, with emotions playing an instrumental role for the sustenance of social norms and social norms being an essential element of regulation in the individual emotional system. This paper lays the foundations for a computational study of this interrelationship, drawing upon the functional appraisal theory of emotions. We describe a first implementation of a situated agent architecture, TABASCOJAM, that incorporates a simple appraisal mechanism and report on its evaluation in a well-known scenario for the study of aggression control as a function of a norm, that was suitably extended. The simulation results reported in the original aggression control study were successfully reproduced, and consistent performances were achieved for extended scenarios with conditional norm obeyance. In conclusion, it is argued that the present effort indicates a promising lane towards the necessary abandonment of logical models for the explanation and simulation of human social behaviour.

How Groups Can Foster Consensus: The Case of Local Cultures

Patrick Groeber, Frank Schweitzer and Kerstin Press
Journal of Artificial Societies and Social Simulation 12 (2) 4

Kyeywords: Social Norms, Conventions, Bounded Confidence, Dynamic Networks
Abstract: A local culture denotes a set of rules on business behaviour among firms in a cluster. Similar to social norms or conventions, it is an emergent feature of interaction in an economic network. To model its emergence, we consider a distributed agent population, representing cluster firms. Further, we build on a continuous opinion dynamics model with bounded confidence (ε), which assumes that two agents only interact if differences in their behaviour are less than ε. Interaction results in more similarity of behaviour, i.e. convergence towards a common mean. Two aspects extend this framework: (i) The agent\'s in-group consisting of acquainted interaction partners is explicitly taken into account, leading to an effective agent behaviour as agents try to continue to interact with past partners and thus seek to stay sufficiently close to them. (ii) The in-group network structure changes over time, as agents form new links to other agents with sufficiently close effective behaviour or delete links to agents no longer close in behaviour. Thus, the model introduces a feedback mechanism of agent behaviour and in-group structure. Studying its consequences by means of agent-based computer simulations, we find that for narrow-minded agents (low ε) the feedback mechanism helps find consensus more often, whereas for open-minded agents (high ε) this does not necessarily hold. Overall, the dynamics of agent interaction in clusters as modelled here, are conducive to consensus among all or a majority of agents.

Obligation Norm Identification in Agent Societies

Tony Bastin Roy Savarimuthu, Stephen Cranefield, Maryam A. Purvis and Martin K. Purvis
Journal of Artificial Societies and Social Simulation 13 (4) 3

Kyeywords: Norms, Social Norms, Obligations, Norm Identification, Agent-Based Simulation, Simulation of Norms, Artificial Societies, Normative Multi-Agent Systems (NorMAS)
Abstract: Most works on norms have investigated how norms are regulated using institutional mechanisms. Very few works have focused on how an agent may infer the norms of a society without the norm being explicitly given to the agent. This paper describes a mechanism for identifying one type of norm, an obligation norm. The Obligation Norm Inference (ONI) algorithm described in this paper makes use of an association rule mining approach to identify obligation norms. Using agent based simulation of a virtual restaurant we demonstrate how an agent can identify the tipping norm. The experiments that we have conducted demonstrate that an agent in the system is able to add, remove and modify norms dynamically. An agent can also flexibly modify the parameters of the system based on whether it is successful in identifying a norm.

Social Simulation That 'Peers into Peer Review'

Flaminio Squazzoni and Károly Takács
Journal of Artificial Societies and Social Simulation 14 (4) 3

Kyeywords: Peer Review, Social Simulation, Social Norms, Selection Biases, Science Policy
Abstract: This article suggests to view peer review as a social interaction problem and shows reasons for social simulators to investigate it. Although essential for science, peer review is largely understudied and current attempts to reform it are not supported by scientific evidence. We suggest that there is room for social simulation to fill this gap by spotlighting social mechanisms behind peer review at the microscope and understanding their implications for the science system. In particular, social simulation could help to understand why voluntary peer review works at all, explore the relevance of social sanctions and reputational motives to increase the commitment of agents involved, cast light on the economic cost of this institution for the science system and understand the influence of signals and social networks in determining biases in the reviewing process. Finally, social simulation could help to test policy scenarios to maximise the efficacy and efficiency of various peer review schemes under specific circumstances and for everyone involved.

The Big Impact of Small Groups on College Drinking

Ben Fitzpatrick, Jason Martinez, Elizabeth Polidan and Ekaterini Angelis
Journal of Artificial Societies and Social Simulation 18 (3) 4

Kyeywords: Group Formation, Peer Influence, Identity Control Theory, Social Norms, College Drinking
Abstract: College drinking is a problem with severe academic, health, and safety consequences. The underlying social processes that lead to increased drinking activity are not well understood. Social Norms Theory is an approach to analysis and intervention based on the notion that students’ misperceptions about the drinking culture on campus lead to increases in alcohol use. In this paper we develop an agent-based simulation model, implemented in MATLAB, to examine college drinking. Students’ drinking behaviors are governed by their identity (and how others perceive it) as well as peer influences, as they interact in small groups over the course of a drinking event. Our simulation results provide some insight into the potential effectiveness of interventions such as social norms marketing campaigns.

The Effects of Network Structure on the Emergence of Norms in Adaptive Populations

Peter Revay
Journal of Artificial Societies and Social Simulation 18 (4) 14

Kyeywords: Social Norms, Agent-Based Modeling, Social Networks, Neighborhood Structure, Cooperation
Abstract: The different ways individuals socialize with others affect the conditions under which social norms are able to emerge. In this work an agent-based model of cooperation in a population of adaptive agents is presented. The model has the ability to implement a multitude of network topologies. The agents possess strategies represented by boldness and vengefulness values in the spirit of Axelrod's (1986) norms game. However, unlike in the norms game, the simulations abandon the evolutionary approach and only follow a single-generation of agents who are nevertheless able to adapt their strategies based on changes in their environment. The model is analyzed for potential emergence or collapse of norms under different network and neighborhood configurations as well as different vigilance levels in the agent population. In doing so the model is found able to exhibit interesting emergent behavior suggesting potential for norm establishment even without the use of so-called metanorms. Although the model shows that the success of the norm is dependent on the neighborhood size and the vigilance of the agent population, the likelihood of norm collapse is not monotonically related to decreases in vigilance.

Growing Unpopular Norms

Christoph Merdes
Journal of Artificial Societies and Social Simulation 20 (3) 5

Kyeywords: Social Norms, Agent-Based Simulation, Social Influence, Pluralistic Ignorance
Abstract: Unpopular norms are a pervasive and puzzling phenomenon of the social world. They are norms that are established and maintained against the interest of their subjects, but without external coercion. Pluralistic ignorance has been suggested as a potential explanation of unpopular norms. What is currently lacking is a formal model of this process that can be meaningfully compared with empirically known properties of pluralistic ignorance. An agent-based model of a growing social network can reproduce the most significant qualitative features, viz a deviation of the perceived norm from the preference distribution and the dynamical lag of the former behind the latter. In addition, the model is extended with a central influence representing for example central media or a powerful political elite.

Social Norms and the Dominance of Low-Doers

Carlo Proietti and Antonio Franco
Journal of Artificial Societies and Social Simulation 21 (1) 6

Kyeywords: Agent-Based Model, Social Norms, Game Theory
Abstract: Social norms play a fundamental role in holding groups together. The rationale behind most of them is to coordinate individual actions into a beneficial societal outcome. However, there are cases where pro-social behavior within a community seems, to the contrary, to cause inefficiencies and suboptimal collective outcomes. An explanation for this is that individuals in a society are of different types and their type determines the norm of fairness they adopt. Not all such norms are bound to be beneficial at the societal level. When individuals of different types meet a clash of norms can arise. This, in turn, can determine an advantage for the “wrong” type. We show this by a game-theoretic analysis in a very simple setting. To test this result - as well as its possible remedies - we also devise a specific simulation model. Our model is written in NETLOGO and is a first attempt to study our problem within an artificial environment that simulates the evolution of a society over time.