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Revealing the Relational Mechanisms of Research for Development Through Social Network Analysis
Marina Apgar1, Guillaume Fournie2, Barbara Haesler2
1Institute of Development Studies, University of Sussex, Library Road, Falmer, Brighton, BN1 9RE East Sussex UK.
Social network analysis (SNA) can reveal interaction structures in research for development (R4D) programs. This evaluation method helps understand network evolution and supports learning and accountability in R4D initiatives.
Area of Science:
- Social Sciences
- Development Studies
- Evaluation Science
Background:
- Research for Development (R4D) programs require multi-stakeholder engagement for impact.
- Understanding R4D program outcomes necessitates examining relational dynamics and collaboration.
- Social Network Analysis (SNA) is increasingly used to evaluate complex research collaborations.
Purpose of the Study:
- To explore the potential of Social Network Analysis (SNA) as an evaluation method for R4D programs.
- To analyze the application of SNA in evaluating three Interdisciplinary Hubs of the Global Challenges Research Fund.
- To understand how SNA can uncover structural dimensions and network evolution in R4D initiatives.
Main Methods:
- Comparative case study analysis of three R4D programs.
- Application of Social Network Analysis (SNA) within program evaluations.
- Examination of network structures, interactions, and evolution over time.
Main Results:
- SNA effectively visualizes and analyzes the structural properties of interactions within R4D programs.
- SNA facilitates learning about how networks change and evolve throughout the R4D program lifecycle.
- Identified common challenges including data bias, scale interpretation, and ethical considerations in causal inference.
Conclusions:
- SNA offers valuable insights into the relational dynamics crucial for R4D program impact.
- Lessons learned provide guidance for integrating SNA into Monitoring, Evaluation, and Learning (MEL) systems.
- SNA supports both learning objectives and accountability requirements within R4D program evaluations.
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