Recommending the Most Encompassing Opposing and Endorsing Arguments in Debates
This addresses the challenge of information overload in participatory platforms like DirectDemocracyP2P, though it appears incremental as it applies existing graph methods to a specific domain.
The paper tackles the problem of recommending the most comprehensive supporting and opposing arguments in online debates, proposing solutions based on weighted bipartite graphs to identify key justifications for new voters and compact lists that cover most known arguments.
Arguments are essential objects in DirectDemocracyP2P, where they can occur both in association with signatures for petitions, or in association with other debated decisions, such as bug sorting by importance. The arguments of a signer on a given issue are grouped into one single justification, are classified by the type of signature (e.g., supporting or opposing), and can be subject to various types of threading. Given the available inputs, the two addressed problems are: (i) how to recommend the best justification, of a given type, to a new voter, (ii) how to recommend a compact list of justifications subsuming the majority of known arguments for (or against) an issue. We investigate solutions based on weighted bipartite graphs.