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Big Data and Happiness

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  • Rossouw, Stephanie
  • Greyling, Talita

Abstract

The pursuit of happiness. What does that mean? Perhaps a more prominent question to ask is, 'how does one know whether people have succeeded in their pursuit'? Survey data, thus far, has served us well in determining where people see themselves on their journey. However, in an everchanging world, one needs high-frequency data instead of data released with significant time-lags. High-frequency data, which stems from Big Data, allows policymakers access to virtually real-time information that can assist in effective decision-making to increase the quality of life for all. Additionally, Big Data collected from, for example, social media platforms give researchers unprecedented insight into human behaviour, allowing significant future predictive powers.

Suggested Citation

  • Rossouw, Stephanie & Greyling, Talita, 2020. "Big Data and Happiness," GLO Discussion Paper Series 634, Global Labor Organization (GLO).
  • Handle: RePEc:zbw:glodps:634
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    File URL: https://www.econstor.eu/bitstream/10419/223012/1/GLO-DP-0634.pdf
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    References listed on IDEAS

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    5. Hills, Thomas & Proto, Eugenio & Sgroi, Daniel, 2015. "Historical Analysis of National Subjective Wellbeing Using Millions of Digitized Books," IZA Discussion Papers 9195, Institute of Labor Economics (IZA).
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    7. Steyn, Dimitri H. W. & Greyling, Talita & Rossouw, Stephanie & Mwamba, John M., 2020. "Sentiment, emotions and stock market predictability in developed and emerging markets," GLO Discussion Paper Series 502, Global Labor Organization (GLO).
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    Cited by:

    1. Rossouw, Stephanie & Greyling, Talita & Adhikari, Tamanna, 2021. "New Zealand's happiness and COVID-19: a Markov Switching Dynamic Regression Model," GLO Discussion Paper Series 573 [rev.], Global Labor Organization (GLO).
    2. Tiziana Carpi & Airo Hino & Stefano Maria Iacus & Giuseppe Porro, 2020. "On a Japanese Subjective Well-Being Indicator Based on Twitter data," Papers 2012.14372, arXiv.org.
    3. Tiziana Carpi & Airo Hino & Stefano Maria Iacus & Giuseppe Porro, 2021. "Twitter Subjective Well-Being Indicator During COVID-19 Pandemic: A Cross-Country Comparative Study," Papers 2101.07695, arXiv.org.

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    More about this item

    Keywords

    Happiness; Big Data; Sentiment analysis;
    All these keywords.

    JEL classification:

    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software
    • I31 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General Welfare, Well-Being
    • I39 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Other
    • J18 - Labor and Demographic Economics - - Demographic Economics - - - Public Policy

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