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Is the person-situation debate important for agent-based modeling and vice-versa?

Sznajd-Weron K, Szwabiński J, Weron R - PLoS ONE (2014)

Bottom Line: Studying two variants of the same agent-based model of opinion formation, we show that the decision to choose either personal traits or the situation as the primary factor driving social interactions is of critical importance.Using Monte Carlo simulations (for Barabasi-Albert networks) and analytic calculations (for a complete graph) we provide evidence that assuming a person-specific response to social influence at the microscopic level generally leads to a completely different and less realistic aggregate or macroscopic behavior than an assumption of a situation-specific response; a result that has been reported by social psychologists for a range of experimental setups, but has been downplayed or ignored in the opinion dynamics literature.This sensitivity to modeling assumptions has far reaching consequences also beyond opinion dynamics, since agent-based models are becoming a popular tool among economists and policy makers and are often used as substitutes of real social experiments.

View Article: PubMed Central - PubMed

Affiliation: Institute of Physics, Wrocław University of Technology, Wrocław, Poland.

ABSTRACT

Background: Agent-based models (ABM) are believed to be a very powerful tool in the social sciences, sometimes even treated as a substitute for social experiments. When building an ABM we have to define the agents and the rules governing the artificial society. Given the complexity and our limited understanding of the human nature, we face the problem of assuming that either personal traits, the situation or both have impact on the social behavior of agents. However, as the long-standing person-situation debate in psychology shows, there is no consensus as to the underlying psychological mechanism and the important question that arises is whether the modeling assumptions we make will have a substantial influence on the simulated behavior of the system as a whole or not.

Methodology/principal findings: Studying two variants of the same agent-based model of opinion formation, we show that the decision to choose either personal traits or the situation as the primary factor driving social interactions is of critical importance. Using Monte Carlo simulations (for Barabasi-Albert networks) and analytic calculations (for a complete graph) we provide evidence that assuming a person-specific response to social influence at the microscopic level generally leads to a completely different and less realistic aggregate or macroscopic behavior than an assumption of a situation-specific response; a result that has been reported by social psychologists for a range of experimental setups, but has been downplayed or ignored in the opinion dynamics literature.

Significance: This sensitivity to modeling assumptions has far reaching consequences also beyond opinion dynamics, since agent-based models are becoming a popular tool among economists and policy makers and are often used as substitutes of real social experiments.

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Related in: MedlinePlus

Sample Barabasi-Albert network structures for different densities of links, represented by parameter M.The agents are described by a single binary variable and called spinsons to reflect the dyadic nature of the agent (spin) and the object of study (person). The spinson size is proportional to the number of outgoing links, the color (and simultaneously orientation) represent the binary opinion.
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pone-0112203-g001: Sample Barabasi-Albert network structures for different densities of links, represented by parameter M.The agents are described by a single binary variable and called spinsons to reflect the dyadic nature of the agent (spin) and the object of study (person). The spinson size is proportional to the number of outgoing links, the color (and simultaneously orientation) represent the binary opinion.

Mentions: To investigate the above issue we use q-voter models, which have been originally proposed as situation-oriented [20] but can be easily reformulated to become personality-oriented. We set to reflect the empirically observed fact that a group of four individuals sharing the same opinion has a high chance to 'convince' the fifth, even if no rational arguments are available [33], [34]. The agents in our models are described by a single binary variable, which may correspond to 'yes' or 'no' in the field of opinion dynamics or 'adopted' and 'not adopted' when modeling innovation diffusion. For such a simple agent, Nyczka and Sznajd-Weron [20] have recently introduced the name spinson, which reflects the dyadic nature of the agent (spin) and the object of study (person), see Fig. 1. We use this name throughout the paper as it nicely allows to go around gender issues. It should be also emphasized that models like the one discussed here are particularly useful in the field of diffusion of innovation [6], [8], [35]. Hence, in the remainder of the paper we use the 'innovation diffusion' language.


Is the person-situation debate important for agent-based modeling and vice-versa?

Sznajd-Weron K, Szwabiński J, Weron R - PLoS ONE (2014)

Sample Barabasi-Albert network structures for different densities of links, represented by parameter M.The agents are described by a single binary variable and called spinsons to reflect the dyadic nature of the agent (spin) and the object of study (person). The spinson size is proportional to the number of outgoing links, the color (and simultaneously orientation) represent the binary opinion.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4219838&req=5

pone-0112203-g001: Sample Barabasi-Albert network structures for different densities of links, represented by parameter M.The agents are described by a single binary variable and called spinsons to reflect the dyadic nature of the agent (spin) and the object of study (person). The spinson size is proportional to the number of outgoing links, the color (and simultaneously orientation) represent the binary opinion.
Mentions: To investigate the above issue we use q-voter models, which have been originally proposed as situation-oriented [20] but can be easily reformulated to become personality-oriented. We set to reflect the empirically observed fact that a group of four individuals sharing the same opinion has a high chance to 'convince' the fifth, even if no rational arguments are available [33], [34]. The agents in our models are described by a single binary variable, which may correspond to 'yes' or 'no' in the field of opinion dynamics or 'adopted' and 'not adopted' when modeling innovation diffusion. For such a simple agent, Nyczka and Sznajd-Weron [20] have recently introduced the name spinson, which reflects the dyadic nature of the agent (spin) and the object of study (person), see Fig. 1. We use this name throughout the paper as it nicely allows to go around gender issues. It should be also emphasized that models like the one discussed here are particularly useful in the field of diffusion of innovation [6], [8], [35]. Hence, in the remainder of the paper we use the 'innovation diffusion' language.

Bottom Line: Studying two variants of the same agent-based model of opinion formation, we show that the decision to choose either personal traits or the situation as the primary factor driving social interactions is of critical importance.Using Monte Carlo simulations (for Barabasi-Albert networks) and analytic calculations (for a complete graph) we provide evidence that assuming a person-specific response to social influence at the microscopic level generally leads to a completely different and less realistic aggregate or macroscopic behavior than an assumption of a situation-specific response; a result that has been reported by social psychologists for a range of experimental setups, but has been downplayed or ignored in the opinion dynamics literature.This sensitivity to modeling assumptions has far reaching consequences also beyond opinion dynamics, since agent-based models are becoming a popular tool among economists and policy makers and are often used as substitutes of real social experiments.

View Article: PubMed Central - PubMed

Affiliation: Institute of Physics, Wrocław University of Technology, Wrocław, Poland.

ABSTRACT

Background: Agent-based models (ABM) are believed to be a very powerful tool in the social sciences, sometimes even treated as a substitute for social experiments. When building an ABM we have to define the agents and the rules governing the artificial society. Given the complexity and our limited understanding of the human nature, we face the problem of assuming that either personal traits, the situation or both have impact on the social behavior of agents. However, as the long-standing person-situation debate in psychology shows, there is no consensus as to the underlying psychological mechanism and the important question that arises is whether the modeling assumptions we make will have a substantial influence on the simulated behavior of the system as a whole or not.

Methodology/principal findings: Studying two variants of the same agent-based model of opinion formation, we show that the decision to choose either personal traits or the situation as the primary factor driving social interactions is of critical importance. Using Monte Carlo simulations (for Barabasi-Albert networks) and analytic calculations (for a complete graph) we provide evidence that assuming a person-specific response to social influence at the microscopic level generally leads to a completely different and less realistic aggregate or macroscopic behavior than an assumption of a situation-specific response; a result that has been reported by social psychologists for a range of experimental setups, but has been downplayed or ignored in the opinion dynamics literature.

Significance: This sensitivity to modeling assumptions has far reaching consequences also beyond opinion dynamics, since agent-based models are becoming a popular tool among economists and policy makers and are often used as substitutes of real social experiments.

Show MeSH
Related in: MedlinePlus