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Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/32837

Title: Using LIWC to choose simulation approaches: A feasibility study
Authors: McHaney, Roger
Tako, Antuela A.
Robinson, Stewart
Keywords: Linguistic inquiry and word count(LIWC)
Text analytics
Problem solving
Tool choice
Discrete event simulation
System dynamics
Issue Date: 2018
Publisher: © Elsevier
Citation: MCHANEY, R., TAKO, A.A. and ROBINSON, S., 2018. Using LIWC to choose simulation approaches: A feasibility study. Decision Support Systems, 111, pp. 1-12.
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.
Description: This paper is in closed access until 19th October 2019
Version: Accepted for publication
DOI: 10.1016/j.dss.2018.04.002
URI: https://dspace.lboro.ac.uk/2134/32837
Publisher Link: https://doi.org/10.1016/j.dss.2018.04.002
ISSN: 0167-9236
Appears in Collections:Closed Access (Business)

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