This is the third in a series of three symposia that discuss societal challenges in computational social sciences. In 2019, the focus will be on “Polarization and Radicalization” (Zurich, 2019). In the previous two years, the focus was “Inequality and Imbalance” (London, 2017) and “Bias and Discrimination” (Cologne, 2018).
With these three events we provide a platform to address one of the most pressing challenges in today’s digital society: understanding the role that digital technologies, the Web, and the algorithms used therein play in the mediation and creation of inequalities, discrimination and polarization.
By addressing inequality as the topical issue for the symposium series we intend to explore how CSS can contribute to opening up new ways of thinking about, of measuring, detecting and coping with social inequality, discrimination, and polarization. We will discuss how divides and inequalities are proliferated in digital society, how social cleavages can be observed via web data, how the organizational structure of the web itself generates biases and inequality, and how, in contrast, algorithms and computational tools might help to reduce discrimination and inequality. We will also investigate how bias and unequal social structures foster political tension and polarization, including issues of radicalization and hate.
The Euro CSS 2019 will be a three-day event consisting of:
- a two-day, single-track conference featuring a series of invited talks that will provide different perspectives on challenges in the area of Polarization and Radicalization
- a day of multiple satellite events, including workshops and tutorials
- an open call for contributed presentations that will provide opportunities for computational social scientists to present and discuss their own work
- an open call for workshop and tutorial organization that will provide opportunities for computational social scientists to gather focus groups around the latest trends in computational social science
- a dataset challenge to encourage creative engagement with the data from different perspectives and dialogue across disciplines
- plenty of possibilities for interdisciplinary networking (e.g. science slam)