Mental Models Analysis and Comparison Based on Fuzzy Rules: A Case Study of the Protests of June and July 2013 in Brazil

Abstract

Collective decision processes involve a large number of decision makers, demanding the consensus of different points of view about problems of several knowledge areas. The analysis and comparison of these points of view can contribute to this consensus, but they depend on the representation of each decision maker's individual knowledge about the problem. Mental models (MMs) are diagrammatic artifacts based on natural language which can be used to represent such knowledge. These models comprise logical cause-effect loops that are used to describe a problem as understood by each decision maker. This paper proposes an innovative tool based on a knowledge-based system of fuzzy rules which identifies MMs that best represent the consensus about the causes of a specific problem. Fuzzy rules were created, taking into account both, qualitative and quantitative variables. The tool was applied to the analysis and comparison of MMs of university students to describe the protests that occurred in Brazil between June and July 2013. A comparison of results using Pareto analysis indicated that the tool identifies those MMs that best indicate the probable causes of the protests.