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Go back and connect the changes of surnames, or measure social mobility rates: algorithms are a big help in the field of Guido Alfani, Associate Professor of economic history

Since the computer has become the microscope of social scientists, economic historians have seen new horizons open. The availability of increasingly content-rich databases has led to the need to automate operations that were once performed by researchers themselves. "In studies of social mobility or population genetics", says Guido Alfani, Associate Professor of Economic History, "algorithms enable us to connect surnames that have changed over time".

There is more. Alfani is Principal Investigator in "Economic inequality across Italy and Europe, 1300-1800", a project promoted by the Dondena Centre for Research on Social Dynamics and Public Policy. In this project, the algorithms identify wealth classes and measure social mobility rates over the long run, comparing databases that may include hundreds of thousands of people. "One of the key factors in the growth of historical databases is the development of the so-called digital humanities. There has been a stunning development of text recognition algorithms, which allowed researchers to digitalize huge amounts of historical written works, even handwritten ones. The use of algorithms has allowed researchers to process historical sources that were previously considered inherently qualitative such as missives".

Some scholars criticize the massive use of quantitative methods and consider it detrimental to the quality of research in Economic History. "We must never forget the importance of the in-depth knowledge of the sources. A qualitative study leads to a better understanding of historical processes and stimulates insight by providing hypotheses that can be tested with new algorithms. It can be a virtuous circle".

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