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Well-being through the lens of the internet

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  • Yann Algan
  • Fabrice Murtin
  • Elizabeth Beasley
  • Kazuhito Higa
  • Claudia Senik

Abstract

We build models to estimate well-being in the United States based on changes in the volume of internet searches for different words, obtained from the Google Trends website. The estimated well-being series are weighted combinations of word groups that are endogenously identified to fit the weekly subjective well-being measures collected by Gallup Analytics for the United States or the biannual measures for the 50 states. Our approach combines theoretical underpinnings and statistical analysis, and the model we construct successfully estimates the out-of-sample evolution of most subjective well-being measures at a one-year horizon. Our analysis suggests that internet search data can be a complement to traditional survey data to measure and analyze the well-being of a population at high frequency and local geographic levels. We highlight some factors that are important for well-being, as we find that internet searches associated with job search, civic participation, and healthy habits consistently predict well-being across several models, datasets and use cases during the period studied.

Suggested Citation

  • Yann Algan & Fabrice Murtin & Elizabeth Beasley & Kazuhito Higa & Claudia Senik, 2019. "Well-being through the lens of the internet," PLOS ONE, Public Library of Science, vol. 14(1), pages 1-23, January.
  • Handle: RePEc:plo:pone00:0209562
    DOI: 10.1371/journal.pone.0209562
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    Cited by:

    1. Rossouw, Stephanie & Greyling, Talita & Adhikari, Tamanna & Morrison, Phillip S., 2020. "Markov switching models for happiness during a pandemic: The New-Zealand experience," GLO Discussion Paper Series 573, Global Labor Organization (GLO).
    2. Jean-Alain Héraud & Phu Nguyen-Van & Thi Kim Cuong Pham, 2020. "Public services and subjective well-being in a European city: The case of Strasbourg metropolitan area," Working Papers of BETA 2020-21, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    3. Greyling, Talita & Rossouw, Stephanie & Adhikari, Tamanna, 2020. "A tale of three countries: How did Covid-19 lockdown impact happiness?," GLO Discussion Paper Series 584, Global Labor Organization (GLO).
    4. Fulvio Castellacci & Henrik Schwabe, 2020. "Internet, unmet aspirations and the U-shape of life," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-22, June.
    5. Weerakkody, Vishanth & Sivarajah, Uthayasankar & Mahroof, Kamran & Maruyama, Takao & Lu, Shan, 2021. "Influencing subjective well-being for business and sustainable development using big data and predictive regression analysis," Journal of Business Research, Elsevier, vol. 131(C), pages 520-538.
    6. 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).
    7. Kaur, Puneet & Dhir, Amandeep & Tandon, Anushree & Alzeiby, Ebtesam A. & Abohassan, Abeer Ahmed, 2021. "A systematic literature review on cyberstalking. An analysis of past achievements and future promises," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    8. Evgeniy SHCHEKOTIN & Mikhail MYAGKOV & Viacheslav GOIKO & Vitaliy KASHPUR, 2021. "Digital Methods Of Analysis Of Subjective Quality Of Life: Case Of Russian Regions," REVISTA ADMINISTRATIE SI MANAGEMENT PUBLIC, Faculty of Administration and Public Management, Academy of Economic Studies, Bucharest, Romania, vol. 2021(36), pages 25-48, June.

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