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We have discussed why we form relationships, what attracts us to others, and different types of love. But what determines whether we are satisfied with and stay in a relationship? One theory that provides an explanation is social exchange theory. According to social exchange theory, we act as naïve economists in keeping a tally of the ratio of costs and benefits of forming and maintaining a relationship with others (Rusbult & Van Lange, 2003).
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Using social network analysis as a tool in action research.

Susan Paterson1, Elizabeth E W McInerney1, Scotney D Evans1

  • 1Department of Educational and Psychological Studies, University of Miami, Coral Gables, Florida, USA.

Journal of Community Psychology
|March 24, 2022
PubMed
Summary

Social network analysis (SNA) assessed connectivity in three South Florida collaboratives. Findings varied, highlighting challenges and power dynamics in organizational networks.

Keywords:
action researchcollective impactnonprofit organizationsorganizational collaborativespowersocial justicesocial network analysis

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Area of Science:

  • Social Sciences
  • Community Research
  • Network Analysis

Background:

  • Community collaboratives are crucial for addressing complex social issues.
  • Understanding organizational connectivity is key to effective collective action.
  • Social network analysis (SNA) offers a quantitative approach to map and analyze these connections.

Purpose of the Study:

  • To demonstrate the application of SNA in evaluating connectivity within diverse community coalitions.
  • To explore the utility of SNA as an action research tool in real-world collaborative settings.
  • To identify challenges and the influence of power dynamics in organizational networks.

Main Methods:

  • Case study approach examining three distinct South Florida collaboratives: youth homelessness, university student concerns, and social justice.
  • Social network analysis (SNA) employed to assess the frequency of communication and connectivity between organizations.
  • Data analysis utilized Gephi for two collaboratives and R for network centrality in another.

Main Results:

  • Varying levels of connectivity were observed across the three case examples.
  • The frequency of inter-organizational communication served as a primary indicator of network cohesion.
  • Specific software (Gephi, R) was used for network visualization and centrality measurements.

Conclusions:

  • SNA provides valuable insights into the structure and dynamics of community collaboratives.
  • Challenges exist in applying SNA as an action research tool, including data collection and interpretation.
  • Power dynamics among organizations significantly influence network structure and collaborative effectiveness.