Augmenting business statistics information by combining traditional data with textual data: a composite indicator approach

被引:0
|
作者
Camilla Salvatore
Silvia Biffignandi
Annamaria Bianchi
机构
[1] Utrecht University,Department of Methodology and Statistics
[2] Consultant in Economic Statistics Studies,Department of Economics
[3] University of Bergamo,undefined
来源
METRON | 2024年 / 82卷
关键词
Socio-economic indicators; Mazziotta–Pareto index; Sustainable development; Social media; Twitter;
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学科分类号
摘要
Combining traditional and digital trace data is an emerging trend in statistics. In this respect, new data sources represent the basis for multi-purpose extraction of different statistical indicators, which contribute to augmenting the statistical information, for feeding smart statistics. The production of business statistics can benefit from the use of unstructured data, especially to study novel aspects which are not covered by traditional data sources. This paper proposes a methodological general framework for augmenting information by combining data, both structured and non structured. The statistical challenges of using unstructured data and their integration with traditional data are discussed. The methodological general framework is applied to the construction of smart composite indicators using social media data and their metadata. An empirical exercise illustrates how to apply the methodology in practice.
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页码:71 / 91
页数:20
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