Structuring the Use of Social Network Analysis in Program Evaluation
2022-12
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Structuring the Use of Social Network Analysis in Program Evaluation
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2022-12
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Social network analysis (SNA) is increasingly viewed as a contributing methodology to program evaluation to examine the complexities of social programs and interrelationships within the program networks. Despite the growing literature on the topic, more knowledge is needed to understand how, when, and under what conditions social network analysis can add value to evaluation work. The study's overall purpose was to explore the ways of applying SNA to support program evaluation. Using a sequential mixed method social network analysis (MMSNA) approach, this study first developed the SNA-Evaluation framework based on existing literature. Guided by the SNA-Evaluation framework, this study applied the SNA method to support the evaluation of the Community-Based Opioid Prevention and Education (C.O.P.E.) program. Data for the study were collected through a review of 30 archival documents, a C.O.P.E. Partnership Network survey to 46 partner organizations, and semi-structured interviews of 8 program stakeholders. The results suggested that evaluators can adopt the SNA method to support their evaluation practices depending on the types of evaluation, such as needs assessment, process evaluation, and outcome evaluation. The study also observed that the use of SNA in the field of evaluation, particularly for responding to complex social programs, can sharpen program theories, strengthen evaluation methods by enabling the assessment of complex adaptive system variables, and maximize evaluation instrumental and conceptual use. The study contributes to the body of research on evaluation methods by exploring an alternative methodology that can add value to evaluation practice. The study benefits the knowledge base in program evaluation by providing the SNA-Evaluation framework and screening tool to help evaluators determine more appropriate steps when applying the SNA method to support their evaluation work. This study has implications for evaluators (1) who have an interest in improving their SNA use in program evaluation, (2) who hope to explore more about the theories behind the use of the SNA method in program evaluation, and (3) who support the evaluation of complex social programs.
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University of Minnesota Ph.D. dissertation. December 2022. Major: Organizational Leadership, Policy, and Development. Advisor: David Johnson. 1 computer file (PDF); xii, 216 pages.
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Zhang, Lixin. (2022). Structuring the Use of Social Network Analysis in Program Evaluation. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/253417.
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