Well-being through the lens of the internet.

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 su...

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Main Authors: Yann Algan, Fabrice Murtin, Elizabeth Beasley, Kazuhito Higa, Claudia Senik
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2019-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0209562
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author Yann Algan
Fabrice Murtin
Elizabeth Beasley
Kazuhito Higa
Claudia Senik
author_facet Yann Algan
Fabrice Murtin
Elizabeth Beasley
Kazuhito Higa
Claudia Senik
author_sort Yann Algan
collection DOAJ
description 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.
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spelling doaj.art-d98ec3c8d1a04e14aa53f73c8c8ba9b72022-12-21T22:36:50ZengPublic Library of Science (PLoS)PLoS ONE1932-62032019-01-01141e020956210.1371/journal.pone.0209562Well-being through the lens of the internet.Yann AlganFabrice MurtinElizabeth BeasleyKazuhito HigaClaudia SenikWe 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.https://doi.org/10.1371/journal.pone.0209562
spellingShingle Yann Algan
Fabrice Murtin
Elizabeth Beasley
Kazuhito Higa
Claudia Senik
Well-being through the lens of the internet.
PLoS ONE
title Well-being through the lens of the internet.
title_full Well-being through the lens of the internet.
title_fullStr Well-being through the lens of the internet.
title_full_unstemmed Well-being through the lens of the internet.
title_short Well-being through the lens of the internet.
title_sort well being through the lens of the internet
url https://doi.org/10.1371/journal.pone.0209562
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