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Background <p>Social relationships are shaped by a complex interplay of interests and emotions, making negative interactions inevitable. Research on negative bias and loss aversion demonstrates that people are more sensitive to negative interactions, which often leads to social distancing. However, one study found that individuals with anxious attachment styles may actively seek partners who treat them poorly, suggesting that such relationships can strengthen bonds. But the cognitive mechanisms underlying how negative relationships can signal positive relational outcomes remain unclear. Through five experiments, we examine how shared negative relationships help individuals infer positive relationships and explore the underlying mechanisms.</p> Methods <p>We conducted five pre-registered experiments (N = 1,085; <i>M</i><sub>age</sub> = 20.22, <i>SD</i> = 2.05) using hypothetical scenarios and social network methodologies. In Experiment 1, participants inferred interpersonal relationships from images depicting shared negative relationships. Building on this, Experiment 2 specifically focused on images of bidirectional shared negative relationships. Experiment 3 extended this paradigm to the intergroup level, where participants inferred relationships between groups based on shared negative relationships with a third-party. Experiment 4 refined this focus by examining in-group and out-group dynamics, asking participants to infer relationships from images of shared negative relationships between members of these distinct groups. Finally, Experiment 5 employed a simulated social network paradigm in which participants inferred relationships by learning and remembering social knowledge within an incomplete network, thus modeling real-world social inference under uncertainty.</p> Results <p>Our results showed that humans can (a) infer positive relationships from shared negative ones and their quantity; (b) adjust these inferences by group size and contextual boundaries—shifting from resource-based inferring in ambiguous settings to identity-based mechanisms in well-defined groups; and (c) shape network representations from incomplete social knowledge, revealing human differences in cognitive mechanisms.</p> Conclusions <p>While negative relationships can weaken social experiences, shared negative interactions can serve as prosocial tools for inferring positive relationships. Research shows that humans adjust their strategies based on relationship quantity and group structure, enabling them to build networks from incomplete social knowledge.</p>

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Shared enemies as prosocial tool: how to infer positive relationships from negative relationships in social networks

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年2月13日

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  • Yating Chen,
  • Leping Wang,
  • Qiang Zhou

摘要

Background

Social relationships are shaped by a complex interplay of interests and emotions, making negative interactions inevitable. Research on negative bias and loss aversion demonstrates that people are more sensitive to negative interactions, which often leads to social distancing. However, one study found that individuals with anxious attachment styles may actively seek partners who treat them poorly, suggesting that such relationships can strengthen bonds. But the cognitive mechanisms underlying how negative relationships can signal positive relational outcomes remain unclear. Through five experiments, we examine how shared negative relationships help individuals infer positive relationships and explore the underlying mechanisms.

Methods

We conducted five pre-registered experiments (N = 1,085; Mage = 20.22, SD = 2.05) using hypothetical scenarios and social network methodologies. In Experiment 1, participants inferred interpersonal relationships from images depicting shared negative relationships. Building on this, Experiment 2 specifically focused on images of bidirectional shared negative relationships. Experiment 3 extended this paradigm to the intergroup level, where participants inferred relationships between groups based on shared negative relationships with a third-party. Experiment 4 refined this focus by examining in-group and out-group dynamics, asking participants to infer relationships from images of shared negative relationships between members of these distinct groups. Finally, Experiment 5 employed a simulated social network paradigm in which participants inferred relationships by learning and remembering social knowledge within an incomplete network, thus modeling real-world social inference under uncertainty.

Results

Our results showed that humans can (a) infer positive relationships from shared negative ones and their quantity; (b) adjust these inferences by group size and contextual boundaries—shifting from resource-based inferring in ambiguous settings to identity-based mechanisms in well-defined groups; and (c) shape network representations from incomplete social knowledge, revealing human differences in cognitive mechanisms.

Conclusions

While negative relationships can weaken social experiences, shared negative interactions can serve as prosocial tools for inferring positive relationships. Research shows that humans adjust their strategies based on relationship quantity and group structure, enabling them to build networks from incomplete social knowledge.