Measuring happiness increases happiness

Jannik Roessler () and Peter A. Gloor ()
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Jannik Roessler: University of Cologne
Peter A. Gloor: Massachusetts Institute of Technology

Journal of Computational Social Science, 2021, vol. 4, issue 1, No 6, 123-146

Abstract: 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.

Keywords: Emotion prediction; Wearable technology; Smartwatch; Machine learning; Heisenberg effect (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s42001-020-00069-6

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