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Conversational agents, also known as chatbots, are versatile tools that havethe potential of being used in dialogical argumentation. They could possibly bedeployed in tasks such as persuasion for behaviour change (e.g. persuadingpeople to eat more fruit, to take regular exercise, etc.) However, to achievethis, there is a need to develop methods for acquiring appropriate argumentsand counterargument that reflect both sides of the discussion. For instance, topersuade someone to do regular exercise, the chatbot needs to knowcounterarguments that the user might have for not doing exercise. To addressthis need, we present methods for acquiring arguments and counterarguments, andimportantly, meta-level information that can be useful for deciding whenarguments can be used during an argumentation dialogue. We evaluate thesemethods in studies with participants and show how harnessing these methods in achatbot can make it more persuasive.

Impact of Argument Type and Concerns in Argumentation with a Chatbot