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Types of Selection01:46

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Natural selection influences the frequencies of particular alleles and phenotypes within populations in several different ways. Primarily, natural selection can be directional, stabilizing, or disruptive. Directional selection favors one extreme trait and shifts the population towards that phenotype while selecting against individuals displaying alternate traits. Stabilizing selection favors an intermediate trait with a narrow range of variation. Deviation from the optimal phenotype towards an...
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Bidirectional selection between two classes in complex social networks.

Bin Zhou1, Zhe He2, Luo-Luo Jiang3

  • 11] Department of Modern Physics, University of Science and Technology of China, Hefei, 230026, China [2] School of Economics and Management, Jiangsu University of Science and Technology, Zhenjiang, 212003, China.

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Bidirectional selection, common in social life, is influenced by network neighborhoods. Higher network degrees increase successful matching, with small-world networks outperforming scale-free ones.

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Area of Science:

  • Social network analysis
  • Game theory
  • Sociology

Background:

  • Bidirectional selection is prevalent in social interactions like trading and mate choice.
  • Limited research exists on bidirectional selection within structured human societies.
  • Understanding matching mechanisms in complex social networks is crucial.

Purpose of the Study:

  • To theoretically investigate the impact of social network structure on bidirectional selection.
  • To analyze how network properties influence successful matching rates.
  • To compare matching performance across different network topologies.

Main Methods:

  • Theoretical modeling of bidirectional selection processes.
  • Analysis of matching rates based on network characteristics (e.g., neighborhood, degree).
  • Quantitative investigation of matching performance in various network types (small-world, scale-free).

Main Results:

  • Individual neighborhoods significantly affect successful matching rates, irrespective of network type.
  • Increased average network degree positively correlates with higher successful matching rates.
  • Small-world networks demonstrate enhanced matching rates compared to scale-free networks at equivalent average degrees.

Conclusions:

  • Social network structure is a critical determinant of bidirectional selection success.
  • Network topology, particularly small-world characteristics, can optimize matching processes.
  • The study provides theoretical insights into the mechanisms governing matching in complex social systems.