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A Year of Pandemic: Levels, Changes and Validity of Well-Being Data from Twitter. Evidence from Ten Countries

Author

Listed:
  • Sarracino, Francesco

    (University of California)

  • Greyling, Talita

    (University of Johannesburg)

  • O'Connor, Kelsey J.

    (STATEC Research – National Institute of Statistics and Economic Studies)

  • Peroni, Chiara

    (STATEC Research – National Institute of Statistics and Economic Studies)

  • Rossouw, Stephanié

    (Auckland University of Technology)

Abstract

In this article, we describe how well-being changed during 2020 in ten countries, namely Australia, Belgium, France, Germany, Great Britain, Italy, Luxembourg, New Zealand, South Africa, and Spain. Our measure of well-being is the Gross National Happiness (GNH), a country-level index built applying sentiment analysis to data from Twitter. We aim to describe how GNH changed during the pandemic within countries, assess its validity as a measure of well-being, and analyse its correlations. We take advantage of a unique dataset of daily observations about GNH, generalised trust and trust in national institutions, fear concerning the economy, loneliness, infection rate, policy stringency and distancing. To assess the validity of the data sourced from Twitter, we exploit various survey data sources, such as the Eurobarometer and consumer satisfaction, and Big Data sources, such as Google Trends. Results indicate that sentiment analysis of tweets can provide reliable and timely information on well-being. This can be particularly useful to timely inform decision-making.

Suggested Citation

  • Sarracino, Francesco & Greyling, Talita & O'Connor, Kelsey J. & Peroni, Chiara & Rossouw, Stephanié, 2021. "A Year of Pandemic: Levels, Changes and Validity of Well-Being Data from Twitter. Evidence from Ten Countries," IZA Discussion Papers 14903, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp14903
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    References listed on IDEAS

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    Cited by:

    1. Francesco Sarracino & Kelsey J. O’Connor, 2023. "Neo-humanism and COVID-19: Opportunities for a socially and environmentally sustainable world," Applied Research in Quality of Life, Springer;International Society for Quality-of-Life Studies, vol. 18(1), pages 9-41, February.
    2. Sarracino, Francesco & Greyling, Talita & O'Connor, Kelsey J. & Peroni, Chiara & Rossouw, Stephanié, 2022. "Trust Predicts Compliance with COVID-19 Containment Policies: Evidence from Ten Countries Using Big Data," IZA Discussion Papers 15171, Institute of Labor Economics (IZA).
    3. Greyling, Talita & Rossouw, Stephanié, 2022. "Re-examining adaptation theory using Big Data: Reactions to external shocks," GLO Discussion Paper Series 1129, Global Labor Organization (GLO).
    4. Francesco Sarracino & Talita Greyling & Kelsey J. O'Connor & Chiara Peroni & Stephanie Rossouw, 2021. "Trust predicts compliance to Covid-19 containment policies: evidence from ten countries using big data," Department of Economics University of Siena 858, Department of Economics, University of Siena.

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    More about this item

    Keywords

    happiness; COVID-19; Big Data; Twitter; Sentiment Analysis; well-being; public policy; trust; fear; loneliness;
    All these keywords.

    JEL classification:

    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • I10 - Health, Education, and Welfare - - Health - - - General
    • I31 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General Welfare, Well-Being
    • H12 - Public Economics - - Structure and Scope of Government - - - Crisis Management

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