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stefano's BibTeX entry:  

Distributed Factors in the Development of Popularity (or 'Why Doesn't Anybody Like Me?')

2006.
Authors: Terry Stewart and Robert L. West and Robert Coplan
Tags: cognition networks social
Abstract: Individual factors by no means completely account for individual popularity within a group structure. To begin to explain the majority of the variance, we must investigate the hypothesis that popularity is strongly influenced by the dynamics of group interactions. Here, we present a computational model of peer interaction that allows us to investigate the influence of different distributed factors. In constructing the model, we discovered that certain elements are vital for the simulation to produce data that matches the observed patterns in real social groups. We found that the internal representation of how much agents like each other must be discrete, that judgements should be made relative to behavioural expectations, and that models do not require variation in the initial state of the agents to produce realistic individual differences in popularity. Our result is a set of models with psychologically realistic attributes. When simulated, these models result in popularity data that cannot be reliably distinguished from real life data. Since these models capture the essential dynamics of the social group interaction, they can form the basis for understanding how interaction within the group influences individuals to become popular or rejected.
| BibTeX  
@unpublished{Stewart_2006_Popularity,
title = {Distributed Factors in the Development of Popularity (or 'Why Doesn't Anybody Like Me?')},
author = {Terry Stewart and Robert L. West and Robert Coplan},
year = {2006},
abstract = {Individual factors by no means completely account for individual popularity within a group structure. To begin to explain the majority of the variance, we must investigate the hypothesis that popularity is strongly influenced by the dynamics of group interactions. Here, we present a computational model of peer interaction that allows us to investigate the influence of different distributed factors. In constructing the model, we discovered that certain elements are vital for the simulation to produce data that matches the observed patterns in real social groups. We found that the internal representation of how much agents like each other must be discrete, that judgements should be made relative to behavioural expectations, and that models do not require variation in the initial state of the agents to produce realistic individual differences in popularity. Our result is a set of models with psychologically realistic attributes. When simulated, these models result in popularity data that cannot be reliably distinguished from real life data. Since these models capture the essential dynamics of the social group interaction, they can form the basis for understanding how interaction within the group influences individuals to become popular or rejected. },
keywords = {cognition networks social }
}