Advanced statistical analysis of large-scale Web-based data

Wienke Strathern, Raji Ghawi, Jürgen Pfeffer

People leave millions of digital traces in the big data ecosystem. This ecosystem is a huge network with millions of daily personal transactions. And each of these transactions leaves traces that may be compiled into comprehensive information about individual and group behaviour (Lazer et al 2009, 2020). The capacity to collect huge amounts of data transforms the way people and organisations work and behave; hence, the market starts to react faster and increasingly anticipates traditional or other data sources. Data-driven computational economics capture changes in market, attitude and consumer behaviour over time and in real time. The quantitative techniques of machine learning have been applied to demonstrate a shift from a discretionary to a quantitative investment style (Kolanovic and Krishnamachari 2017). An increasing share of human interaction, communication and culture is recorded as digital text. Text is used as an input to economic research. Statistical methods and deep learning methods are applied to digital texts, as such data provides a rich repository of information about economic and social activity (Gentzkow et al 2019; Gentzkow and Shapiro 2010). More interesting

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