Periodic Reporting for period 1 - SoMe4Dem (Social media for democracy – understanding the causal mechanisms of digital citizenship)
Período documentado: 2023-03-01 hasta 2024-02-29
reference point: the (implicit) reference to the dysfunctional constitution of the political public sphere which
is currently undergoing structural change. The rise of social media platforms is considered as one of its main
constituents. While social media make the public arena more open and thus more responsive, these platforms also
lead to new mechanisms of fragmentation and exclusion, an erosion of norms in public debate and a loss of trust in
traditional institutions.
The project will reconsider the diagnoses of this crisis by (1) providing better empirical evidence for the impact
of social media on society with respect to political debates, (2) understanding the main causal mechanisms of this
impact and (3) developing tools that improve the capacity of social media to contribute to the functioning of the
public arena in a liberal democracy, i.e. deliberation, legitimation and the self-perception of the democratic subject.
In order to provide better empirical evidence for discussing the impact of social media the project aims for methodological innovations in a) measurement, b) experimentation and c) modelling. In the first year we created data-set containing an attitudinal embedding of a sample of Twitter users from 9 European states along two dimension (Left-Right, Anti-Elite) in order to study the interaction between polarization and trust. We started pilots for the experiments on the relationship between participation and polarization and on the impact of social media on trust. In the context of modeling the dynamics on and of social media platforms we stablished our general framework for model validation.
Finally, we produced first insights regarding improving the design of social media platforms: In an ongoing study on existing Twitter data we observed promising results fort the use of exogenous cues for improving recommendation algorithms.