Content Analysis Using Fuzzy Cognitive Map (FCM) A Guide to Capturing Causal Relationships from Secondary Sources of Data
Cognitive mapping was introduced as a method to model complex systems that reflects how experts or stakeholders understand cause and effect relationships. Later, fuzzy cognitive mapping (FCM) combined cognitive mapping with artificial neural networks (ANN) resulting in the unique capacity to capture and use qualitative data to perform quantitative analysis and study system behavior in response to changes of system elements. However, when it comes to building FCM models from qualitative data, particularly from secondary data sources, guidance for modelers is scarce. This article introduces a step by step guideline for building FCM that not only deals with causal relationships but also offers techniques to adjust the inconsistencies, and tune the granularities through parent child relationships. It also proposes two techniques, isolated graph analysis, and receiver only concept analysis to investigate the completeness of the final FCM and hypothesize new connections to fill the gaps.
2017 Portland International Conference on Management of Engineering and Technology (PICMET)