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arXiv · 2207.13508

Challenges and Opportunities of Computational Social Science for Official Statistics

Serena Signorelli·Matteo Fontana·Lorenzo Gabrielli·Michele Vespe
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Abstract

The vast amount of data produced everyday (so-called 'digital traces') and available nowadays represent a gold mine for the social sciences, especially in a computational context, that allows to fully extract their informational and knowledge value. In the latest years, statistical offices have made efforts to profit from harnessing the potential offered by these new sources of data, with promising results. But how difficult is this integration process? What are the challenges that statistical offices would likely face to profit from new data sources and analytical methods? This chapter will start by setting the scene of the current official statistics system, with a focus on its fundamental principles and dimensions relevant to the use of non-traditional data. It will then present some experiments and proofs of concept in the context of data innovation for official statistics, followed by a discussion on prospective challenges related to sustainable data access, new technical and methodological approaches and effective use of new sources of data.

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Serena Signorelli, Matteo Fontana, Lorenzo Gabrielli, Michele Vespe. 2022-07-27. Challenges and Opportunities of Computational Social Science for Official Statistics. https://doi.org/10.1007/978-3-031-16624-2_10

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