Social Network Analysis Methods for Higher Education Development [CIES Presentation]

Social network analysis methods for international development: Applications in higher education development. Social Network Analysis (SNA) is a promising yet underutilized tool in the international development field. SNA entails collecting and analyzing data to characterize and visualize social networks, where nodes represent network members and edges connecting nodes represent relationships or exchanges among them. SNA can help both researchers and practitioners understand the social, political, and economic relational dynamics at the heart of international development programming. It can inform program design, monitoring, and evaluation to answer questions related to where people get information; with whom goods and services are exchanged; who people value, trust, or respect; who has power and influence and who is excluded; and how these dynamics change over time. This brief advances the case for use of SNA in international development, outlines general approaches, and discusses two recently conducted case studies in higher education development that illustrate its potential. It concludes with recommendations for how to increase SNA use in international development. Key research recommendations advanced by this paper include: • Incorporate SNA into monitoring, evaluation, and learning processes. SNA can be conducted at various points of a project to inform program design, adaptive management, learning, and evaluation by considering network structure and network changes over time. • Demystify the use of SNA. Increased use of SNA tools and clear presentation in widely read publications are needed to bring the analytic approach into the mainstream of international development. • Build capacity to conduct SNA. The capacity to conduct and interpret SNA is lacking across actors in international development. Efforts by some organizations to build capacity in the community are well noted and should be built upon. • Build understanding of relationships between social networks and development outcomes. SNA will be useful only to the extent it helps users understand the relationship between networks and development outcomes that matter. • Establish norms for data collection and identity protection. Data about individuals and their interactions with others are inherently sensitive data. As a part of standard research ethics protocols, SNA practitioners must make carefully considered decisions about how or if to anonymize data when reporting it.