Cultural Evolution, Disinformation, and Social Division

Author:

Bentley R Alexander1ORCID,Horne Benjamin2,Borycz Joshua3ORCID,Carrignon Simon4ORCID,Shteynberg Garriy5,Vidiella Blai6ORCID,Valverde Sergi67,O’Brien Michael J89

Affiliation:

1. College of Emerging and Collaborative Studies, University of Tennessee, Knoxville, TN, USA

2. School of Information Sciences, University of Tennessee, Knoxville, TN, USA

3. Sarah Shannon Stevenson Science and Engineering Library, Vanderbilt University, Nashville, TN, USA

4. Department of Archaeology, University of Cambridge, Cambridge, TN, UK

5. Department of Psychology, University of Tennessee, Knoxville, TN, USA

6. Evolution of Networks Lab, Institute of Evolutionary Biology (UPF-CSIC), Universitat Autònoma de Barcelona, Barcelona, Spain

7. European Centre for Living Technology (ECLT), Ca’ Bottacin, Italy

8. Department of History and Philosophy and Department of Life Sciences, Texas A&M University–San Antonio, TX, USA

9. Department of Anthropology, University of Missouri, Columbia, MO, USA

Abstract

Diversity of expertise is inherent to cultural evolution. When it is transparent, diversity of human knowledge is useful; when social conformity overcomes that transparency, “expertise” can lead to divisiveness. This is especially true today, where social media has increasingly allowed misinformation to spread by prioritizing what is recent and popular, regardless of validity or general benefit. Whereas in traditional societies there was diversity of expertise, contemporary social media facilitates homophily, which isolates true subject experts from each other and from the wider population. Diversity of knowledge thus becomes social division. Here, we discuss the potential of a cultural-evolutionary framework designed for the countless choices in contemporary media. Cultural-evolutionary theory identifies key factors that determine whether communication networks unify or fragment knowledge. Our approach highlights two parameters: transparency of information and social conformity. By identifying online spaces exhibiting aggregate patterns of high popularity bias and low transparency of information, we can help define the “safe limits” of social conformity and information overload in digital communications.

Publisher

SAGE Publications

Subject

Behavioral Neuroscience,Experimental and Cognitive Psychology

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