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      Are Opinions Based on Science: Modelling Social Response to Scientific Facts

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          Abstract

          As scientists we like to think that modern societies and their members base their views, opinions and behaviour on scientific facts. This is not necessarily the case, even though we are all (over-) exposed to information flow through various channels of media, i.e. newspapers, television, radio, internet, and web. It is thought that this is mainly due to the conflicting information on the mass media and to the individual attitude (formed by cultural, educational and environmental factors), that is, one external factor and another personal factor. In this paper we will investigate the dynamical development of opinion in a small population of agents by means of a computational model of opinion formation in a co-evolving network of socially linked agents. The personal and external factors are taken into account by assigning an individual attitude parameter to each agent, and by subjecting all to an external but homogeneous field to simulate the effect of the media. We then adjust the field strength in the model by using actual data on scientific perception surveys carried out in two different populations, which allow us to compare two different societies. We interpret the model findings with the aid of simple mean field calculations. Our results suggest that scientifically sound concepts are more difficult to acquire than concepts not validated by science, since opposing individuals organize themselves in close communities that prevent opinion consensus.

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          Empirical analysis of an evolving social network.

          Social networks evolve over time, driven by the shared activities and affiliations of their members, by similarity of individuals' attributes, and by the closure of short network cycles. We analyzed a dynamic social network comprising 43,553 students, faculty, and staff at a large university, in which interactions between individuals are inferred from time-stamped e-mail headers recorded over one academic year and are matched with affiliations and attributes. We found that network evolution is dominated by a combination of effects arising from network topology itself and the organizational structure in which the network is embedded. In the absence of global perturbations, average network properties appear to approach an equilibrium state, whereas individual properties are unstable.
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            Coevolutionary games - a mini review

            , (2010)
            Prevalence of cooperation within groups of selfish individuals is puzzling in that it contradicts with the basic premise of natural selection. Favoring players with higher fitness, the latter is key for understanding the challenges faced by cooperators when competing with defectors. Evolutionary game theory provides a competent theoretical framework for addressing the subtleties of cooperation in such situations, which are known as social dilemmas. Recent advances point towards the fact that the evolution of strategies alone may be insufficient to fully exploit the benefits offered by cooperative behavior. Indeed, while spatial structure and heterogeneity, for example, have been recognized as potent promoters of cooperation, coevolutionary rules can extend the potentials of such entities further, and even more importantly, lead to the understanding of their emergence. The introduction of coevolutionary rules to evolutionary games implies, that besides the evolution of strategies, another property may simultaneously be subject to evolution as well. Coevolutionary rules may affect the interaction network, the reproduction capability of players, their reputation, mobility or age. Here we review recent works on evolutionary games incorporating coevolutionary rules, as well as give a didactic description of potential pitfalls and misconceptions associated with the subject. In addition, we briefly outline directions for future research that we feel are promising, thereby particularly focusing on dynamical effects of coevolutionary rules on the evolution of cooperation, which are still widely open to research and thus hold promise of exciting new discoveries.
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              Generic absorbing transition in coevolution dynamics.

              We study a coevolution voter model on a complex network. A mean-field approximation reveals an absorbing transition from an active to a frozen phase at a critical value [see text for formula] that only depends on the average degree micro of the network. In finite-size systems, the active and frozen phases correspond to a connected and a fragmented network, respectively. The transition can be seen as the sudden change in the trajectory of an equivalent random walk at the critical point, resulting in an approach to the final frozen state whose time scale diverges as tau approximately |p(c) - p|(-)} near p(c).
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2012
                8 August 2012
                : 7
                : 8
                : e42122
                Affiliations
                [1 ]Department of Biomedical Engineering and Computational Science, Aalto University School of Science, Helsinki, Finland
                [2 ]Centro de Investigación en Energa, Universidad Nacional Autónoma de México, Temixco, Morelos, Mexico
                [3 ]Instituto de Fsica, Universidad Nacional Autónoma de México, México Distrito Federal, Mexico
                Umeå University, Sweden
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: GI JTM KKK RAB. Performed the experiments: GI RAB. Analyzed the data: GI JTM RAB. Contributed reagents/materials/analysis tools: JTM. Wrote the paper: GI JTM KKK RAB.

                Article
                PONE-D-12-06450
                10.1371/journal.pone.0042122
                3414539
                22905117
                83de04e3-ab20-47e0-b540-0b270deb7c47
                Copyright @ 2012

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 27 February 2012
                : 2 July 2012
                Page count
                Pages: 12
                Funding
                GI and KK acknowledge the Academy of Finland, the Finnish Center of Excellence program 2006–2011, under Project No. 129670. KK acknowledges support from EU’s FP7 FET Open STREP Project ICTeCollective No. 238597. KK and RAB want to acknowledge financial support from Conacyt through Project No. 79641. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Computer Science
                Numerical Analysis
                Mathematics
                Applied Mathematics
                Complex Systems
                Mathematical Computing
                Nonlinear Dynamics
                Physics
                Interdisciplinary Physics
                Statistical Mechanics
                Science Policy
                Science Education
                Social and Behavioral Sciences
                Sociology
                Computational Sociology
                Social Networks

                Uncategorized
                Uncategorized

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