City Research Online

Supporting Theoretically-grounded Model Building in the Social Sciences through Interactive Visualisation

Turkay, C., Slingsby, A., Lahtinen, K., Butt, S. and Dykes, J. (2017). Supporting Theoretically-grounded Model Building in the Social Sciences through Interactive Visualisation. Neurocomputing, 268, pp. 153-163. doi: 10.1016/j.neucom.2016.11.087

Abstract

The primary purpose for which statistical models are employed in the social sciences is to understand and explain phenomena occurring in the world around us. In order to be scientifically valid and actionable, the construction of such models need to be strongly informed by theory. To accomplish this, there is a need for methodologies that can enable scientists to utilise their domain knowledge effectively even in the absence of strong a priori hypotheses or whilst dealing with complex datasets containing hundreds of variables and leading to large numbers of potential models. In this paper, we describe enhanced model building processes in which we use interactive visualisations as the underlying mechanism to facilitate the construction and documentation of theory-driven models. We report our observations from a collaborative project involving social and computer scientists, and identify key roles for visualisation to support model building within the context of social science. We describe a suite of techniques to facilitate the exploration of statistical summaries of input variables, to compare the quality of alternative models, and to keep track of the model-building process. We demonstrate how these techniques operate in coordination to allow social scientists to efficiently generate models that are tightly underpinned by domain specific theory.

Publication Type: Article
Additional Information: © 2017, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/
Publisher Keywords: visualization, visual analytics, model building, social science
Subjects: H Social Sciences > HM Sociology
Q Science > QA Mathematics
Departments: School of Arts & Social Sciences > Sociology
School of Mathematics, Computer Science & Engineering > Computer Science > giCentre
URI: http://openaccess.city.ac.uk/id/eprint/16153
[img]
Preview
Text - Accepted Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.

Download (5MB) | Preview

Export

Downloads

Downloads per month over past year

View more statistics

Actions (login required)

Admin Login Admin Login