Collective Social Dynamics and Social Norms
AbstractHow individual behaviour is determined or at least influenced by social norms is one of the classic questions of social theory. We consider a norm as a rule guiding individual decisions concerning rituals, beliefs, traditions, and routines. Whenever coordinated behaviour is enforced without the help of an authority, this may be due to social norms. The individual being in the situation of taking a decision at the micro level is guided by social norms imposed at the macro level. The set of all individual decisions in a society generates the macro level behaviour of the system which may strengthen or weaken the existing social norms. Thus, the long run development of social norms is the result of collective dynamics within a social network. We use an agent based simulation model to investigate the emergence, stability, and replacement of social norms within a population of artificial agents. A social network connecting the agents serves to communicate the social norms and the actual behaviour among the agent population. The agents in the network possess two types of links connecting them with their ingroup and with their outgroup, respectively. Agents have the desire to be associated and accepted by the members of their ingroup and they want to be different from the members of their outgroup. Consequently, they derive a utility from adhering to the social norm of their ingroup and from deviating from the social norm of their outgroup. Agents may adopt their behaviour according to the norms given by their ingroup and outgroup. Thus, our model explains under what conditions social norms prevail within a subgroup of the society or even become global norms being respected within the whole population.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 2841.
Date of creation: 23 Feb 2006
Date of revision:
social norms; sociel networks; social interaction; collective social dynamics; ingroup; outgroup; agent based modelling;
Find related papers by JEL classification:
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
- C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
- Z13 - Other Special Topics - - Cultural Economics - - - Economic Sociology; Economic Anthropology; Social and Economic Stratification
- D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
This paper has been announced in the following NEP Reports:
- NEP-ALL-2007-04-28 (All new papers)
- NEP-CBE-2007-04-28 (Cognitive & Behavioural Economics)
- NEP-CMP-2007-04-28 (Computational Economics)
- NEP-EVO-2007-04-28 (Evolutionary Economics)
- NEP-NET-2007-04-28 (Network Economics)
- NEP-SOC-2007-04-28 (Social Norms & Social Capital)
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- Макаров В.Л., 2013. "Социальное Моделирование Набирает Обороты," Журнал Экономика и математические методы (ЭММ), Центральный Экономико-Математический Институт (ЦЭМИ), vol. 49(4), pages 5-17, Ð¾ÐºÑÑÐ.
- Marco Campenní & Giulia Andrighetto & Federico Cecconi & Rosaria Conte, 2009. "Normal = Normative? The role of intelligent agents in norm innovation," Mind and Society: Cognitive Studies in Economics and Social Sciences, Fondazione Rosselli, vol. 8(2), pages 153-172, December.
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