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This paper applies a novel technique of opinion analysis over social mediadata with the aim of proposing a new indicator of perceived and subjectivewell-being. This new index, namely SWBI, examines several dimension ofindividual and social life. The indicator has been compared to some otherexisting indexes of well-being and health conditions in Italy: the BES(Benessere Equo Sostenibile), the incidence rate of influenza and the abundanceof PM10 in urban environments. SWBI is a daily measure available at provincelevel. BES data, currently available only for 2013 and 2014, are annual andavailable at regional level. Flu data are weekly and distributed as regionaldata and PM10 are collected daily for different cities. Due to the fact thatthe time scale and space granularity of the different indexes varies, we applya novel statistical technique to discover nowcasting features and the classicallatent analysis to study the relationships among them. A preliminary analysissuggest that the environmental and health conditions anticipate severaldimensions of the perception of well-being as measured by SWBI. Moreover, theset of indicators included in the BES represent a latent dimension ofwell-being which shares similarities with the latent dimension represented bySWBI.

Social networks, happiness and health: from sentiment analysis to a multidimensional indicator of subjective well-being