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      Social network architecture and the tempo of cumulative cultural evolution

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          Abstract

          The ability to build upon previous knowledge—cumulative cultural evolution—is a hallmark of human societies. While cumulative cultural evolution depends on the interaction between social systems, cognition and the environment, there is increasing evidence that cumulative cultural evolution is facilitated by larger and more structured societies. However, such effects may be interlinked with patterns of social wiring, thus the relative importance of social network architecture as an additional factor shaping cumulative cultural evolution remains unclear. By simulating innovation and diffusion of cultural traits in populations with stereotyped social structures, we disentangle the relative contributions of network architecture from those of population size and connectivity. We demonstrate that while more structured networks, such as those found in multilevel societies, can promote the recombination of cultural traits into high-value products, they also hinder spread and make products more likely to go extinct. We find that transmission mechanisms are therefore critical in determining the outcomes of cumulative cultural evolution. Our results highlight the complex interaction between population size, structure and transmission mechanisms, with important implications for future research.

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          Most cited references41

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          Collective dynamics of 'small-world' networks.

          Networks of coupled dynamical systems have been used to model biological oscillators, Josephson junction arrays, excitable media, neural networks, spatial games, genetic control networks and many other self-organizing systems. Ordinarily, the connection topology is assumed to be either completely regular or completely random. But many biological, technological and social networks lie somewhere between these two extremes. Here we explore simple models of networks that can be tuned through this middle ground: regular networks 'rewired' to introduce increasing amounts of disorder. We find that these systems can be highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs. We call them 'small-world' networks, by analogy with the small-world phenomenon (popularly known as six degrees of separation. The neural network of the worm Caenorhabditis elegans, the power grid of the western United States, and the collaboration graph of film actors are shown to be small-world networks. Models of dynamical systems with small-world coupling display enhanced signal-propagation speed, computational power, and synchronizability. In particular, infectious diseases spread more easily in small-world networks than in regular lattices.
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            Birds of a Feather: Homophily in Social Networks

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              The cultural niche: why social learning is essential for human adaptation.

              In the last 60,000 y humans have expanded across the globe and now occupy a wider range than any other terrestrial species. Our ability to successfully adapt to such a diverse range of habitats is often explained in terms of our cognitive ability. Humans have relatively bigger brains and more computing power than other animals, and this allows us to figure out how to live in a wide range of environments. Here we argue that humans may be smarter than other creatures, but none of us is nearly smart enough to acquire all of the information necessary to survive in any single habitat. In even the simplest foraging societies, people depend on a vast array of tools, detailed bodies of local knowledge, and complex social arrangements and often do not understand why these tools, beliefs, and behaviors are adaptive. We owe our success to our uniquely developed ability to learn from others. This capacity enables humans to gradually accumulate information across generations and develop well-adapted tools, beliefs, and practices that are too complex for any single individual to invent during their lifetime.
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                Author and article information

                Contributors
                Journal
                Proc Biol Sci
                Proc Biol Sci
                RSPB
                royprsb
                Proceedings of the Royal Society B: Biological Sciences
                The Royal Society
                0962-8452
                1471-2954
                March 10, 2021
                March 10, 2021
                March 10, 2021
                : 288
                : 1946
                : 20203107
                Affiliations
                [ 1 ]Department for the Ecology of Animal Societies, Max Planck Institute of Animal Behavior, , Am Obstberg 1, Radolfzell 78315, Konstanz, Germany
                [ 2 ]Cognitive and Cultural Ecology Research Group, Max Planck Institute of Animal Behavior, , Am Obstberg 1, Radolfzell 78315, Konstanz, Germany
                [ 3 ]Departamento de Ecologia e Zoologia, Universidade Federal de Santa Catarina, , Florianópolis, Brazil
                [ 4 ]Department of Biology, University of Konstanz, , Konstanz, Germany
                [ 5 ]Centre for the Advanced Study of Collective Behaviour, University of Konstanz, , Konstanz, Germany
                [ 6 ]Department of Human Behavior, Ecology and Culture, Max Planck Institute for Evolutionary Anthropology, , Leipzig, Germany
                [ 7 ]Department of Collective Behaviour, Max Planck Institute of Animal Behavior, , Konstanz, Germany
                [ 8 ]Department of Evolutionary Biology and Environmental Science, University of Zurich, , Zurich, Switzerland
                Author notes
                [†]

                Joint first authors, arranged alphabetically.

                [‡]

                Joint senior authors.

                Electronic supplementary material is available online at https://doi.org/10.6084/m9.figshare.c.5309958.

                Author information
                http://orcid.org/0000-0002-0019-5106
                http://orcid.org/0000-0001-5697-1701
                http://orcid.org/0000-0003-1001-6615
                http://orcid.org/0000-0003-2208-7613
                Article
                rspb20203107
                10.1098/rspb.2020.3107
                7944107
                33715438
                e0cf05c6-b6c3-4243-8811-3a665adc65dc
                © 2021 The Authors.

                Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.

                History
                : December 13, 2020
                : February 8, 2021
                Funding
                Funded by: China Scholarship Council, http://dx.doi.org/10.13039/501100004543;
                Award ID: 201706100183
                Funded by: H2020 European Research Council, http://dx.doi.org/10.13039/100010663;
                Award ID: 850859
                Funded by: Max-Planck-Gesellschaft, http://dx.doi.org/10.13039/501100004189;
                Funded by: Deutsche Forschungsgemeinschaft, http://dx.doi.org/10.13039/501100001659;
                Award ID: EXC 2117–422037984
                Funded by: Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, http://dx.doi.org/10.13039/501100002322;
                Award ID: 88881.170254/2018-01
                Categories
                1001
                70
                14
                Evolution
                Research Articles
                Custom metadata

                Life sciences
                cultural evolution,cultural complexity,multilevel societies,small-world networks,social structure

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