Results & Publications


Measuring deliberative debate quality is an emerging topic in computational work, since it allows applying deliberative democratic ideas in an online domain. When doing so, many studies follow Habermas in defining norms of online deliberative debate quality. They then proceed to propose and test new ways to measure indicators like equality, diversity, interactiveness, rationality, and civility. Consequently, implementing them within recommender systems is the necessary next step to realize those values in online communication. Although this is important work, we argue that recent advances in political science suggest that constructing a system which produces such a deliberative debate is unlikely to, by itself, contribute in an optimal way to deliberative democracy at a societal scale. Instead, we propose a complementary, summative approach to designing deliberative recommender systems. It treats online platforms as complementary to other communication channels, and argues for optimizing how to best facilitate (summative) deliberation at a societal scale rather than perfecting (micro) discussions between citizens. We illustrate this with an example of how a news recommender system based on a summative approach would have to be designed vis-a-vis a more traditional, additive approach.


deliberative democracy, normative standards, online debate quality, computational text analysis, moral recommender systems

Sjoerd B. Stolwijk, Corinna Oschatz, Michael Heseltine, Damian Trilling. 2023. “Redefining Deliberative Standards for Online Poitical Communication: Introducing a Summative Approach to Designing Deliberative Recommender Systems”. NORMalize 2023: The First Workshop on the Normative Design and Evaluation of Recommender Systems, September 19, 2023, co-located with the ACM Conference on Recommender Systems 2023 (RecSys 2023), Singapore

Read the paper here