Understanding Digital Societies


An international research group that includes RWTH Professor Markus Strohmaier is calling for new structures and framework conditions for computational social sciences. Article in Science journal.


Computational Social Sciences (CSS) provide unique insights into social phenomena and the underlying mechanisms of digital societies. The potential but also existing difficulties of computational social sciences are clearly demonstrated with the COVID-19 pandemic. On the one hand, companies are making mobility data from members of the public available anonymously in warning apps, for example, providing important insights into social behavior. On the other hand, this is a particular exception. Computational social sciences are generally lacking in sufficient data because it is fundamentally difficult to collect or only insufficiently provided by private companies.

An international association of researchers including RWTH professor Markus Strohmaier, Chair for Methods and Theories of Computational Social Sciences and Humanities at the Human Technology Center – HumTec, has now explained the obstacles and possibilities of computational social sciences in the journal Science and made clear demands. They emphasize that infrastructures, data exchange, and research ethics must be improved and incentives must be created for this.

Computational social sciences (CSS) have seen enormous development over the past decade. Thousands of publications have been written and phenomena such as social inequality and the spread of infectious diseases such as COVID-19 have been studied using observational data and large-scale simulations.

“CSS comprises the social analysis of language, places, movement, networks, images, and videos using algorithmic procedures, statistical models, and consideration of various dependencies. In this way, computational social sciences expand the spectrum of methods used in traditional social sciences and open up new data-based approaches to the study of digital societies," explains Strohmaier, professor at the Faculty of Mathematics, Computer Science and Natural Sciences as well as the Faculty of Arts and Humanities.

Researchers from the social sciences, computer science, physics, and other disciplines are all involved in computational social sciences. The scholars responsible for the article want to see their cooperation intensified at universities across the country.

The potential of CSS is particularly obvious in light of the pandemic. It could make valuable contributions to national security, the improvement of economic prosperity, the promotion of social inclusion, diversity, and justice, and the strengthening of democracy.

Ultimately, the crucial factor is available data. "Access to data from non-university institutions and private companies is still lacking for academics," explains Strohmaier. And when data is available, issues such as privacy, validity, and whether the data is still current prevail. The authors of the paper are advocating clear guidelines for the ethical use of data, which naturally take into account public values such as privacy, security, human dignity, justice, and autonomy.

To this end, they are calling for structures for greater cooperation between universities, non-university research institutions, and industry in order to advance publicly funded research.

The results should be subject to compliance with data protection and ethical rules. The first examples of open data structures already exist in the Netherlands, and the first infrastructures have also been created at the GESIS Leibniz Institute for the Social Sciences, where Strohmaier is scientific coordinator for Digital Behavioral Data. It is now essential to improve the structures, framework conditions, and guidelines in CSS.

Chair for Computational Social Sciences and Humanities

Read the complete article at Science journal.

Published in:

Science 28 Aug 2020: Vol. 369, Issue 6507, pp. 1060-1062
DOI: 10.1126/science.aaz8170