Natural Language Processing and Social Network Analysis applied on the elaboration of Causal Diagrams

The amount of digital storage data is continuously increasing. This is a challenge and also an opportunity for problem structuring moderators. This article shows how the use of natural language processing and social network analysis can support the moderators on the problem structuring process. A problematic situation of water shortage that affected many regions of the world such as Brazil and United States during the years 2014 and 2015 is used as a case study to show how unstructured data could be analyzed in order to support on the elaboration of causal diagrams. The results show that the above mentioned methods have the potential to improve the quality of the problem structuring by allowing the moderators to take credit of large amounts of information.

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