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Using LIWC to choose simulation approaches: A feasibility study

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journal contribution
posted on 2018-05-04, 12:47 authored by Roger McHaney, Antuela Tako, Stewart Robinson
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.

History

School

  • Business and Economics

Department

  • Business

Published in

Decision Support Systems

Volume

111

Pages

1-12

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.

Publisher

© Elsevier

Version

  • AM (Accepted Manuscript)

Publisher statement

This paper was accepted for publication in the journal Decision Support Systems and the definitive published version is available at https://doi.org/10.1016/j.dss.2018.04.002

Acceptance date

2018-04-17

Publication date

2018-04-19

Copyright date

2018

ISSN

0167-9236

Language

  • en