Equality in Online Deliberation: Can Argument Mapping Facilitation Make Every Voice Count?

Computer scientists have developed argument mining and mapping tools to identify, classify, and interpret argument structures. These tools help scale up citizen deliberation, improve the quality of argumentation, and harvest deliberative outcomes more effectively. However, little is known about how they affect individuals with different personalities or social backgrounds. We investigate whether a novel facilitated form of argument mapping—“argument mapping facilitation”—can improve equality and reduce dominance in synchronous online deliberation. We study an online dialogue on sentencing policy, where participants were randomly assigned to either standard facilitation or enhanced visual facilitation using an argument mapping tool. Based on video observations, surveys, and interviews, we find that argument mapping facilitation improves internal equality by highlighting arguments from minority and less active individuals. It also externalises ownership of arguments, which may make dominant participants less attached to their initial views and more open to reflection. At the same time, the structured and depersonalised nature of mapping risks diminishing the salience of personal narratives and experiential forms of reasoning, suggesting that careful design is needed to ensure these contributions are not displaced. By situating these findings within debates on deliberative and representative democracy, the paper clarifies what is at stake when digital tools mediate the deliberative forums that increasingly inform representative institutions.