Using LIWC to choose simulation approaches: A feasibility study

Abstract

Can language usage help determine which model approach is best suited to provide decision makers with desired insights? This research addresses that question through an investigation of Linguistic Inquiry and Word Count (LIWC), which calculates the presence of more than 80 language dimensions in text samples, and permits construction of custom dictionaries. This article demonstrates use of LIWC to ensure better problem/model fit within the context of selecting a decision support tool. We selected two simulation tools as research instruments to investigate a broader question on the usefulness of LIWC to guide choice of DSS tool. The tools selected were System Dynamics (SD) and Discrete Event Simulation (DES). First, we tested LIWC to analyze practitioners' language use when developing models. LIWC pointed out significant linguistic differences consistent with prior theoretical work, based on model development approach in a number of dimensions. These differences provided a basis for developing a custom dictionary for use on the second part of our study. The second part of the study focused on language used by decision makers in problem statements and used the linguistic clues identified in the first part of the study to ensure problem/model fit. Results indicated problem statements contained linguistic clues related to the type of information desired by problem solvers. The article concludes with a discussion about how LIWC and similar tools can help determine which DSS tools are suited to particular applications.

Examining long-term trends in politics and culture through language of political leaders and cultural institutions

“…Essays with low factor loadings tended to be personal stories (26). Initially labeled the categorical-dynamic index, this pole of the psychological dimension was later renamed analytic (27)(28)(29). Conversely, individuals scoring low on such measures of analytic thinking have been found to use higher rates of function word categories, such as pronouns, negations, auxiliary verbs, and so on-such linguistic features serve as signifiers of a more "intuitive" style of thinking (30,31).…”

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“…We consider four main modelling methods in what follows: discrete event simulation, agent-based modelling, system dynamics and hybrid simulation. It is suggested that the choice of modelling method is made based on decision makers' requirements, type of problem and system complexity and its characteristics (Tako & Robinson, 2009Borshchev & Filippov, 2004;Brennan et al, 2006;Chahal & Eldabi, 2010;McHaney et al, 2018).…”

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