Hunter, A;
Chalaguine, L;
(2021)
Addressing Popular Concerns Regarding COVID-19 Vaccination with Natural Language Argumentation Dialogues.
In:
Symbolic and Quantitative Approaches to Reasoning with Uncertainty. ECSQARU 2021.
(pp. pp. 59-73).
Springer: Cham, Switzerland.
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Abstract
Chatbots have the potential of being used as dialogical argumentation systems for behaviour change applications. They thereby offer a cost-effective and scalable alternative to in-person consultations with health professionals that users could engage in from the comfort of their own home. During events like the global COVID-19 pandemic, it is even more important than usual that people are well informed and make conscious decisions that benefit themselves. Getting a COVID-19 vaccine is a prime example of a behaviour that benefits the individual, as well as society as a whole. In this paper, we present a chatbot that engages in dialogues with users who do not want to get vaccinated, with the goal to persuade them to change their stance and get a vaccine. The chatbot is equipped with a small repository of arguments that it uses to counter user arguments on why the user is reluctant to get a vaccine. We evaluate our chatbot in a study with participants.
| Type: | Proceedings paper |
|---|---|
| Title: | Addressing Popular Concerns Regarding COVID-19 Vaccination with Natural Language Argumentation Dialogues |
| Event: | ECSQARU 2021: Symbolic and Quantitative Approaches to Reasoning with Uncertainty |
| ISBN-13: | 978-3-030-86771-3 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1007/978-3-030-86772-0_5 |
| Publisher version: | https://doi.org/10.1007/978-3-030-86772-0_5 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Chatbots Argumentative persuasion systems, Computational persuasion, Natural language argumentation, Knowledge base construction |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10137297 |
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