八卦
认知地图
构造(python库)
认知
社会世界
心理学
认知科学
社会认知
人际关系
计算机科学
认知心理学
人机交互
数据科学
社会心理学
社会学
社会科学
程序设计语言
神经科学
作者
Oriel FeldmanHall,Jae-Young Son,Apoorva Bhandari
标识
DOI:10.1177/09637214251342742
摘要
How do people represent social networks in their minds? Inspired by work on spatial navigation, recent research reveals how people use domain-general computational principles to build cognitive maps for navigating their social environments. However, some aspects of our social worlds, such as the densely interconnected networks we are embedded in—and the dynamics of information flow within them—challenge the particular construct of a Euclidean cognitive map that has evolved in the study of spatial navigation. Recent research reveals different types of abstract representations people can use to build efficient cognitive maps for navigating social networks. We argue that to solve challenges inherent to navigating social relationships (e.g., figuring out whom to trust or gossip with, building coalitions made up of weak ties), people build cognitive maps of both the direct and indirect relational ties surrounding them. Although the incorporation of indirect ties makes these maps nonveridical, their addition aids in flexible, adaptive behavior, which can be used for successfully navigating any complex social environment.
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