Volume 34, Issue 5 p. 777-793
Special Issue Article
Open Data

Understanding Personality through Patterns of Daily Socializing: Applying Recurrence Quantification Analysis to Naturalistically Observed Intensive Longitudinal Social Interaction Data

Alexander F. Danvers

Corresponding Author

Alexander F. Danvers

Department of Psychology, University of Arizona, Tucson, AZ, USA

Correspondence to: Alexander F. Danvers, University of Arizona, Tucson, AZ, USA.

E-mail: alexander.danvers@gmail.com

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David A. Sbarra

David A. Sbarra

Department of Psychology, University of Arizona, Tucson, AZ, USA

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Matthias R. Mehl

Matthias R. Mehl

Department of Psychology, University of Arizona, Tucson, AZ, USA

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First published: 03 August 2020

Abstract

Ambulatory assessment methods provide a rich approach for studying daily behaviour. Too often, however, these data are analysed in terms of averages, neglecting patterning of this behaviour over time. This paper describes recurrence quantification analysis (RQA), a non-linear time series technique for analysing dynamic systems, as a method for analysing patterns of categorical, intensive longitudinal ambulatory assessment data. We apply RQA to objectively assessed social behaviour (e.g. talking to another person) coded from the Electronically Activated Recorder. Conceptual interpretations of RQA parameters, and an analysis of Electronically Activated Recorder data in adults going through a marital separation, are provided. Using machine learning techniques to avoid model overfitting, we find that adding RQA parameters to models that include just average amount of time spent talking (a static measure) improves prediction of four Big Five personality traits: extraversion, neuroticism, conscientiousness, and openness. Our strongest results suggest that a combination of average amount of time spent talking and four RQA parameters yield an R2 = .09 for neuroticism. Neuroticism is shown to be associated with shorter periods of extended conversation (periods of at least 12 minutes), demonstrating the utility of RQA to identify new relationships between personality and patterns of daily behaviour. Materials: https://osf.io/5nkr9/. © 2020 European Association of Personality Psychology

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This article earned Open Data badge through Open Practices Disclosure from the Center for Open Science: https://osf.io/tvyxz/wiki. The materials are permanently and openly accessible at https://osf.io/5nkr9/. Author's disclosure form may also be found at the Supporting Information in the online version.

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