Date Thesis Awarded

5-2017

Document Type

Honors Thesis

Degree Name

Bachelors of Science (BS)

Department

Interdisciplinary Studies

Advisor

David Aday

Committee Member

Amy Quark

Committee Member

Francie Cate-Arries

Abstract

Collective capacity building is often referenced in the development literature as an integral component of development projects, but few attempts to measure capacity empirically are documented. This research examines social network analysis (SNA) as a way to measure changes in network structure that are indicative of collective capacity. By theorizing about network features that may optimize information flow, I have identified promising network parameters for measuring change over time. By manipulating original SNA data sets from two undergraduate community development projects to promote information flow via network structure, I evaluated the robustness of the proposed network measures. Findings include the identification of breadth, component ratio, connectedness and fragmentation as four network measures that may serve as reliable measures of key changes in collective capacity over time.