Studying Advocacy Coalitions: Conceptual Choices and Methodological Approaches

ABSTRACT Advocacy Coalition Framework (ACF) research has been continuously evolving to improve the understanding of coalition studies. This study aims to critically examine the most common methods for coalition identification in ACF research and to identify strategies to strengthen their clarity and interpretation. We identify and develop ideas around four key steps in using social network analysis (SNA) to study coalitions: collecting and understanding data, choosing a community detection algorithm, applying data transformations, and, most importantly, interpreting community structures. We argue that neither this paper nor any others can provide a definitive approach for understanding advocacy coalitions. Instead, our charge to those using the ACF is threefold. First, recognize the elusiveness of advocacy coalitions and the inherent limitations of any representation. Second, acknowledge that network analysis of advocacy coalitions involves numerous combinatorial choices determined by data characteristics, algorithm selection, and data transformation choices. Third, encourage researchers to understand their data, select among these combinations, interpret results, and effectively communicate the sensitivity and robustness of their analyses.