Universität zu Köln

Peters, J., Wiehler, A. and Bromberg, U. (2017). Quantitative text feature analysis of autobiographical interview data: prediction of episodic details, semantic details and temporal discounting. Sci Rep, 7. LONDON: NATURE PUBLISHING GROUP. ISSN 2045-2322

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Abstract

Autobiographical memory and episodic future thinking (i.e. the capacity to project oneself into an imaginary future) are typically assessed using the Autobiographical Interview (AI). In the AI, subjects are provided with verbal cues (e.g. your wedding day) and are asked to freely recall (or imagine) the cued past (or future) event. Narratives are recorded, transcribed and analyzed using an established manual scoring procedure (Levine et al., 2002). Here we applied automatic text feature extraction methods to a relatively large (n = 86) set of AI data. In a first proof-of-concept approach, we used regression models to predict internal (episodic) and semantic detail sum scores from low-level linguistic features. Across a range of different regression methods, prediction accuracy averaged at about 0.5 standard deviations. Given the known association of episodic future thinking with temporal discounting behavior, i.e. the preference for smaller-sooner over larger-later rewards, we also ran models predicting temporal discounting directly from linguistic features of AI narratives. Here, prediction accuracy was much lower, but involved the same text feature components as prediction of internal (episodic) details. Our findings highlight the potential feasibility of using tools from quantitative text analysis to analyze AI datasets, and we discuss potential future applications of this approach.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Peters, J. UNSPECIFIED UNSPECIFIED UNSPECIFIED Wiehler, A. UNSPECIFIED UNSPECIFIED UNSPECIFIED Bromberg, U. UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-211398
DOI:	10.1038/s41598-017-14433-6
Journal or Publication Title:	Sci Rep
Volume:	7
Date:	2017
Publisher:	NATURE PUBLISHING GROUP
Place of Publication:	LONDON
ISSN:	2045-2322
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language FUTURE THINKING; DECISION-MAKING; ALZHEIMERS-DISEASE; LANGUAGE USE; LIFE-SPAN; MEMORY; DELAY; TIME; CONSTRUCTION; IMPULSIVITY Multiple languages Multidisciplinary Sciences Multiple languages
Refereed:	Yes
URI:	http://kups.ub.uni-koeln.de/id/eprint/21139