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The recent so-called 'data revolution' offers unprecedented opportunities to innovate regional policies. New data sources are being widely used by the scientific community, however their uptake is far from being systematic in the policy cycle, where data innovation can improve territorial impact assessment. This paper presents a survey on the use of non-traditional data in the context of regional policy, together with a case study on real estate markets of three European countries, highlighting the perspectives and limitations of computational social science in regional analysis in terms of data quality and availability.
Gabrielli et al. (Thu,) studied this question.
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