Measuring and Visualising Global Happiness

RR Bond; Shuai Zhang; Fiona Marshall

doi:10.14236/ewic/HCI2018.210

Measuring and Visualising Global Happiness

RR Bond, Shuai Zhang, Fiona Marshall

Research output: Contribution to conference › Paper › peer-review

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Abstract

Happiness scores from the World Happiness Reports have been examined alongside data from the World Health Organisation and the World Bank to show that happiness is an effective measure of well-being. There is a strong correlation between happiness and GDP and other factors such as years of schooling and life expectancy. Using data from the World Health Organisation and World Bank, the happiness of a nation can be predicted with a RMSE of 0.3. Perhaps, predicting the happiness of a community, nation or industry can help inform interactive digital interventions for happiness building. Possible, such measures could also feature as predictors in affective computing contexts or indeed via social media.

Original language	English
Pages	1-5
Number of pages	5
DOIs	https://doi.org/10.14236/ewic/HCI2018.210
Publication status	Accepted/In press - 7 Jun 2018
Event	British HCI Conference 2018 - Belfast, Belfast, Northern Ireland Duration: 2 Jul 2018 → 6 Jul 2018

Conference

Conference	British HCI Conference 2018
Abbreviated title	BHCI2018
Country/Territory	Northern Ireland
City	Belfast
Period	2/07/18 → 6/07/18

Keywords

happiness
GDP
data analytics

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.14236/ewic/HCI2018.210

BHCI-2018_paper_271Author Accepted Manuscript, 809 KB

Cite this

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abstract = "Happiness scores from the World Happiness Reports have been examined alongside data from the World Health Organisation and the World Bank to show that happiness is an effective measure of well-being. There is a strong correlation between happiness and GDP and other factors such as years of schooling and life expectancy. Using data from the World Health Organisation and World Bank, the happiness of a nation can be predicted with a RMSE of 0.3. Perhaps, predicting the happiness of a community, nation or industry can help inform interactive digital interventions for happiness building. Possible, such measures could also feature as predictors in affective computing contexts or indeed via social media.",

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AB - Happiness scores from the World Happiness Reports have been examined alongside data from the World Health Organisation and the World Bank to show that happiness is an effective measure of well-being. There is a strong correlation between happiness and GDP and other factors such as years of schooling and life expectancy. Using data from the World Health Organisation and World Bank, the happiness of a nation can be predicted with a RMSE of 0.3. Perhaps, predicting the happiness of a community, nation or industry can help inform interactive digital interventions for happiness building. Possible, such measures could also feature as predictors in affective computing contexts or indeed via social media.

KW - happiness

KW - GDP

KW - data analytics

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ER -

Measuring and Visualising Global Happiness

Abstract

Conference

Keywords

UN SDGs

Access to Document

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Cite this