Understanding Personality through Patterns of Daily Socializing: Applying Recurrence Quantification Analysis to Naturalistically Observed Intensive Longitudinal Social Interaction Data. Issue 5 (3rd August 2020)
- Record Type:
- Journal Article
- Title:
- Understanding Personality through Patterns of Daily Socializing: Applying Recurrence Quantification Analysis to Naturalistically Observed Intensive Longitudinal Social Interaction Data. Issue 5 (3rd August 2020)
- Main Title:
- Understanding Personality through Patterns of Daily Socializing: Applying Recurrence Quantification Analysis to Naturalistically Observed Intensive Longitudinal Social Interaction Data
- Authors:
- Danvers, Alexander F.
Sbarra, David A.
Mehl, Matthias R. - Editors:
- Rauthmann, John
- Other Names:
- Rauthmann John F. guestEditor.
- Abstract:
- 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 R 2 = .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 ofAbstract: 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 R 2 = .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 … (more)
- Is Part Of:
- European journal of personality. Volume 34:Issue 5(2020)
- Journal:
- European journal of personality
- Issue:
- Volume 34:Issue 5(2020)
- Issue Display:
- Volume 34, Issue 5 (2020)
- Year:
- 2020
- Volume:
- 34
- Issue:
- 5
- Issue Sort Value:
- 2020-0034-0005-0000
- Page Start:
- 777
- Page End:
- 793
- Publication Date:
- 2020-08-03
- Subjects:
- social interaction -- ambulatory assessment -- dynamic systems -- electronically activated recorder -- personality
Personality -- Periodicals
155.2 - Journal URLs:
- https://journals.sagepub.com/loi/ERP ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/per.2282 ↗
- Languages:
- English
- ISSNs:
- 0890-2070
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3829.733800
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 14703.xml