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Social Networks, Happiness and Health: From Sentiment Analysis to a Multidimensional Indicator of Subjective Well-Being

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  • Stefano Maria IACUS
  • Giuseppe PORRO
  • Silvia SALINI
  • Elena SILETTI

Abstract

This paper applies a novel technique of opinion analysis over social media data with the aim of proposing a new indicator of perceived and subjective well-being. This new index, namely SWBI, examines several dimension of individual and social life. The indicator has been compared to some other existing indexes of well-being and health conditions in Italy: the BES (Benessere Equo Sostenibile), the incidence rate of influenza and the abundance of PM10 in urban environments. SWBI is a daily measure available at province level. BES data, currently available only for 2013 and 2014, are annual and available at regional level. Flu data are weekly and distributed as regional data and PM10 are collected daily for different cities. Due to the fact that the time scale and space granularity of the different indexes varies, we apply a novel statistical technique to discover nowcasting features and the classical latent analysis to study the relationships among them. A preliminary analysis suggests that the environmental and health conditions anticipate several dimensions of the perception of well-being as measured by SWBI. Moreover, the set of indicators included in the BES represent a latent dimension of well-being which shares similarities with the latent dimension represented by SWBI.

Suggested Citation

  • Stefano Maria IACUS & Giuseppe PORRO & Silvia SALINI & Elena SILETTI, 2015. "Social Networks, Happiness and Health: From Sentiment Analysis to a Multidimensional Indicator of Subjective Well-Being," Departmental Working Papers 2015-20, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    • Handle: RePEc:mil:wpdepa:2015-20
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    References listed on IDEAS

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    1. Kuhn, Andreas & Lalive, Rafael & Zweimüller, Josef, 2009. "The public health costs of job loss," Journal of Health Economics, Elsevier, vol. 28(6), pages 1099-1115, December.
    2. Chiao, Chaoshin & Hung, Ken & Lee, Cheng F., 2004. "The price adjustment and lead-lag relations between stock returns: microstructure evidence from the Taiwan stock market," Journal of Empirical Finance, Elsevier, vol. 11(5), pages 709-731, December.
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    Cited by:

    1. Iacus Stefano M. & Salini Silvia & Siletti Elena & Porro Giuseppe, 2020. "Controlling for Selection Bias in Social Media Indicators through Official Statistics: a Proposal," Journal of Official Statistics, Sciendo, vol. 36(2), pages 315-338, June.
    2. Osokin, N. & Solntsev, I., 2017. "Constructing a Multidimensional Indicator of Sports Development: the Case of the Football Development Index," Journal of the New Economic Association, New Economic Association, vol. 36(4), pages 135-163.
    3. S. M. Iacus & G. Porro & S. Salini & E. Siletti, 2022. "An Italian Composite Subjective Well-Being Index: The Voice of Twitter Users from 2012 to 2017," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 161(2), pages 471-489, June.
    4. Yukun Zhao & Feng Yu & Bo Jing & Xiaomeng Hu & Ang Luo & Kaiping Peng, 2019. "An Analysis of Well-Being Determinants at the City Level in China Using Big Data," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 143(3), pages 973-994, June.
    5. Silvia Facchinetti & Elena Siletti, 2022. "Well-being Indicators: a Review and Comparison in the Context of Italy," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 159(2), pages 523-547, January.
    6. Siqi Lai & Yifan Zhu & Brian Deal, 2023. "Did COVID-19 Reshape Visitor Preferences in Urban Parks? Investigating Influences on Sentiments in Shanghai, China," Sustainability, MDPI, vol. 15(23), pages 1-16, November.
    7. Federica Cugnata & Silvia Salini & Elena Siletti, 2021. "Deepening Well-Being Evaluation with Different Data Sources: A Bayesian Networks Approach," IJERPH, MDPI, vol. 18(15), pages 1-10, July.

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    More about this item

    Keywords

    Well-being; Sentiment Analysis; Happiness; Health;
    All these keywords.

    JEL classification:

    • I10 - Health, Education, and Welfare - - Health - - - General
    • I31 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General Welfare, Well-Being

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