Open Conference Systems, STATISTICS AND DATA SCIENCE: NEW CHALLENGES, NEW GENERATIONS

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Measuring Wellbeing by extracting Social Indicators from Big Data
Renza Campagni, Lorenzo Gabrielli, Fosca Giannotti, Riccardo Guidotti, Filomena Maggino, Dino Pedreschi

Last modified: 2017-05-19

Abstract


Traditionally, the construction of social indicators is based upon the availability of data collected on purpose (e.g., official statistics, sample surveys). It is a common view that constructing social indicators, in the perspective of measuring wellbeing of countries, can benefit from the availability of new sources of data (e.g., big data). One of the big challenges in dealing with new data sources is related to the possibility of describing complex social phenomena from different perspectives in order to enrich already used indicators and/or build new ones. However, this possibility introduces new issues in constructing indicators. Our study intends to explore how the classical methodology for social indicators construction should be re-considered in light of using data collected for other aims (for example administrative).

In this perspective, the individual sales receipts, collected during the period 2007/13 and made available to our group by a big Italian chain of stores, allow us to explore not only a particular social phenomenon but also the methodological implications in dealing with big data.