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Dyad vs. network effects: Modeling relationships in personal networks using contextual effects.

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This study introduces contextual models to separate individual relationship (dyad) effects from broader social network influences. Findings reveal relationship redundancy boosts job opportunity discussions, while high network redundancy decreases them, supporting social capital theories.

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Area of Science:

  • Social Network Analysis
  • Sociology
  • Computational Social Science

Background:

  • Understanding social capital requires disentangling individual relationship dynamics from network structures.
  • Previous models often conflate dyad-specific and network-level effects.

Purpose of the Study:

  • To propose and demonstrate contextual models for separating dyad and network effects.
  • To analyze the distinct impacts of dyad redundancy and network redundancy on job opportunity discussions.

Main Methods:

  • Utilized multilevel models nesting dyads within personal networks.
  • Incorporated both dyad-level predictors and network-level means into the analysis.
  • Coded models for contextual analysis to measure within-network and network contextual effects.

Main Results:

  • Dyad redundancy positively impacts the number of job opportunities discussed.
  • Network-level average redundancy negatively affects the number of job opportunities discussed.
  • Dyadic and network effects of redundancy operate in opposing directions.

Conclusions:

  • Contextual models effectively disentangle dyad and network influences.
  • Findings support social capital theories, specifically closure (dyad effect) and brokerage (network effect).
  • The structure of social networks significantly moderates the benefits of individual relationship characteristics.