3 research outputs found
A model to support collective reasoning: Formalization, analysis and computational assessment
Inspired by e-participation systems, in this paper we propose a new model to
represent human debates and methods to obtain collective conclusions from them.
This model overcomes drawbacks of existing approaches by allowing users to
introduce new pieces of information into the discussion, to relate them to
existing pieces, and also to express their opinion on the pieces proposed by
other users. In addition, our model does not assume that users' opinions are
rational in order to extract information from it, an assumption that
significantly limits current approaches. Instead, we define a weaker notion of
rationality that characterises coherent opinions, and we consider different
scenarios based on the coherence of individual opinions and the level of
consensus that users have on the debate structure. Considering these two
factors, we analyse the outcomes of different opinion aggregation functions
that compute a collective decision based on the individual opinions and the
debate structure. In particular, we demonstrate that aggregated opinions can be
coherent even if there is a lack of consensus and individual opinions are not
coherent. We conclude our analysis with a computational evaluation
demonstrating that collective opinions can be computed efficiently for
real-sized debates
Citizen support aggregation methods for participatory platforms
In the context of Digital Democracy, online participation platforms have emerged as innovative tools that enable citizens to participate in the decision making of their nation, region, or local government. Users can issue proposals and arguments in favour or against them and they can also support other people’s arguments. This paper proposes two alternative support aggregation methods and applies them into debates conducted in the Decidim platform