Universität zu Köln

Roessler, Jannik and Gloor, Peter A. (2021). Measuring happiness increases happiness. J. Comput. Soc. Sci., 4 (1). S. 123 - 147. LONDON: SPRINGERNATURE. ISSN 2432-2725

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Abstract

Happiness has been an overarching goal of mankind at least since Aristotle spoke of Eudaimonia. However measuring happiness has been elusive and until now has almost exclusively been done by asking survey questions about self-perceived happiness. We propose a novel approach, tracking happiness and stress through changes in body signals with a smartwatch, the Happimeter. It predicts individual emotions from sensor data collected by an Android Wear smartwatch, such as acceleration, heartbeat, and activity. The Happimeter was used over three months in the innovation lab of a bank with 22 employees to measure individual happiness, activity, and stress. The participants were randomly divided into an experimental and a control group of similar size. Both groups wore the watch and entered their subjective happiness, activity and stress levels several times a day. The user-entered ratings were then used to train a machine learning system using the sensors of the smartwatch to subsequently automatically predict happiness, activity, and stress. The experimental group received ongoing feedback about their mood and which activity, sensor signals, or other people, made them happier or unhappier, while the control group did not get any feedback about their predicted and manually entered emotions. Just like in quantum physics we observed a Heisenberg Effect, where the participants made aware of their measurements changed their behavior: Members of the experimental group that received happiness feedback were 16% happier, and 26% more active than the control group at the end of the experiment. No effect was observed for stress.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Roessler, Jannik UNSPECIFIED UNSPECIFIED UNSPECIFIED Gloor, Peter A. UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-574157
DOI:	10.1007/s42001-020-00069-6
Journal or Publication Title:	J. Comput. Soc. Sci.
Volume:	4
Number:	1
Page Range:	S. 123 - 147
Date:	2021
Publisher:	SPRINGERNATURE
Place of Publication:	LONDON
ISSN:	2432-2725
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language Social Sciences, Mathematical Methods Multiple languages
URI:	http://kups.ub.uni-koeln.de/id/eprint/57415