2020
Journal article  Open Access

Measuring objective and subjective well-being: Dimensions and data sources

Voukelatou V., Gabrielli L., Miliou I., Cresci S., Sharma R., Tesconi M., Pappalardo L.

Computational Theory and Mathematics  Modeling and Simulation  Computer Science Applications  Information Systems  mining  Applied Mathematics  social media analysis 

Well-being is an important value for people's lives, and it could be considered as an index of societal progress. Researchers have suggested two main approaches for the overall measurement of well-being, the objective and the subjective well-being. Both approaches, as well as their relevant dimensions, have been traditionally captured with surveys. During the last decades, new data sources have been suggested as an alternative or complement to traditional data. This paper aims to present the theoretical background of well-being, by distinguishing between objective and subjective approaches, their relevant dimensions, the new data sources used for their measurement and relevant studies. We also intend to shed light on still barely unexplored dimensions and data sources that could potentially contribute as a key for public policing and social development.

Source: International Journal of Data Science and Analytics (Print) (2020). doi:10.1007/s41060-020-00224-2

Publisher: Springer


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BibTeX entry
@article{oai:it.cnr:prodotti:424951,
	title = {Measuring objective and subjective well-being: Dimensions and data sources},
	author = {Voukelatou V. and Gabrielli L. and Miliou I. and Cresci S. and Sharma R. and Tesconi M. and Pappalardo L.},
	publisher = {Springer},
	doi = {10.1007/s41060-020-00224-2},
	journal = {International Journal of Data Science and Analytics (Print)},
	year = {2020}
}

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