Comfort or safety? Gathering and using the concerns of a participant for better persuasion

Abstract

Persuasion is an important and yet complex aspect of human intelligence. When undertaken through dialogue, the deployment of good arguments, and therefore counterarguments, clearly has a significant effect on the ability to be successful in persuasion. A key dimension for determining whether an argument is good is the impact that it has on the concerns of the intended audience of the argument (e.g., the other participant(s) in the dialogue). In this paper, we investigate how we can acquire and represent concerns of a participant, and her preferences over them, and we show how this can be used for selecting good moves in a persuasion dialogue. We provide results from empirical studies showing that: (1) we can gather preferences over types of concern; (2) there is a common understanding of what is meant by concerns; (3) participants tend to make moves according to their preferences; and (4) the persuader can use these preferences to improve the persuasiveness of a dialogue.

Computational opposition analysis using word embeddings: A method for strategising resonant informal argument

“…While there has been some interest in bringing computation to semiotics as surveyed in 1.2, and a number of recent papers in automated persuasion [16,17,26,34], we believe the rising pressure on individuals to process the vast number of informal arguments they encounter every day warrants more work in this area. How often, for example, is an argument glimpsed on the internet processed to completion?…”

“…• A sociologist wonders if their article is more likely to be accepted by a British or American journal • A politician wants to know how to best appeal to those on the opposing side of gun control by analysing Twitter data Natural language processing (NLP) provides tools that may assist in such tasks ad hoc by modelling lexical choices and classifying them in terms of relevance, topic, or sentiment, or in specialised components for systems for argument finding and invention [41] or automated persuasion [16,17]. The process of selecting soda can colours, for example, might be aided by analysing social media posts as an exercise in audience analysis.…”

Impact of Argument Type and Concerns in Argumentation with a Chatbot

“…Furthermore, we want to investigate how concerns of the persuadee impact the effectiveness of arguments in persuasion dialogues. The results in [12] show that taking persuadee's concerns into account improves the persuasiveness of a dialogue. The persuader might present a valid argument the persuadee does not disagree with (e.g.…”

“…Eating a lot of saturated fat can raise cholesterol levels, which raises your risk of heart disease" is more likely to change her intention to consume less meat. Whilst this is a simple and intuitive idea, there is a lack of a general framework for using concerns in making strategic choices of move in the way suggested by the above example [12]. A similar notion to concerns are values.…”

Towards Computational Persuasion via Natural Language Argumentation Dialogues

“…We can use crowdsourcing for the acquisition of user models based on concerns [28] and beliefs [36]. To represent and reason with beliefs in arguments, we can use the epistemic approach to probabilistic argumentation [56,32,4,40,48] which has been supported by experiments with participants [47].…”