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Thesis Defense - Bong

Exploring the Semantic Meaning of Constructs that Lead to Human Decisions
Computer Science PhD Candidate

This study examines automated approaches to discovery of behavioral knowledge encoded as constructs in social and behavioral science disciplines. To date, construct relationships are ordinarily revealed through laborious psychometric methods, but this study shows that it is possible to extract these relationships through text-based automated computational approaches. By building on text similarity measures from prior literature, we are able to predict construct relationships through construct name, definition and items. The predicted relationships were woven into an interlocked system to demonstrate construct interplays. The construct interlock could be seen as a theory map to understand human decision-making. Two use cases are presented to demonstrate the efficacy of the proposed measures: measuring the root constructs in Unified Theory of Acceptance and Use of Technology (UTAUT) and visualizing connectivity of the construct perceived usefulness. The results are encouraging and show that the proposed measures could dramatically expedite theory development and improve understanding of human behavior.

Committee: James Martin, Professor (Co-Chair)
Kai Larsen, Leeds School of Business (Co-Chair)
Clayton Lewis, Professor
Tamara Sumner, Associate Professor
Martha Palmer, Professor
Department of Computer Science
University of Colorado Boulder
Boulder, CO 80309-0430 USA
May 5, 2012 (14:20)