Conference Proceedings
Inferring the Mood of a Community From Their Walking Speed: A Preliminary Study
Oludamilare Matthews, Zhanna Sarsenbayeva, Weiwei Jiang, Joshua Newn, Eduardo Velloso, Sarah Clinch, Jorge Goncalves
Association for Computing Machinery | Published : 2018
Abstract
The mood of a community influences work productivity, socioeconomic outcomes and general quality of life of its members, so being able to measure it opens a wealth of opportunities like, informing policies, scheduling events and possibly discovering the contexts that bring about undesirable moods within a community. Though there are a plethora of methods for measuring emotional states of individuals in lab settings (e.g. self-report, analysis of nonverbal behaviours, physiological sensors), they do not scale well to large numbers of people or in-the-wild settings. This paper examines the feasibility of inferring the mood of a community by measuring the walking speed of pedestrians, which is ..
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Awarded by JST ERATO
Funding Acknowledgements
This work was supported by JST ERATO Grant Number JP-MJER1501 and the University of Melbourne-University of Manchester Research Fund.