Debating technology for dialogical argument: sensemaking, engagement, and analytics.

Lawrence, John; Snaith, Mark; Konat, Barbara; Budzynska, Katarzyna; Reed, Chris

Abstract

Debating technologies, a newly emerging strand of research into computational technologies to support human debating, offer a powerful way of providing naturalistic, dialogue-based interaction with complex information spaces. The full potential of debating technologies for dialogical argument can, however, only be realized once key technical and engineering challenges are overcome, namely data structure, data availability, and interoperability between components. Our aim in this article is to show that the Argument Web, a vision for integrated, reusable, semantically rich resources connecting views, opinions, arguments, and debates online, offers a solution to these challenges. Through the use of a running example taken from the domain of citizen dialogue, we demonstrate for the first time that different Argument Web components focusing on sensemaking, engagement, and analytics can work in concert as a suite of debating technologies for rich, complex, dialogical argument.

Citation

LAWRENCE, J., SNAITH, M., KONAT, B., BUDZYNSKA, K. and REED. C. 2017. Debating technology for dialogical argument: sensemaking, engagement, and analytics. ACM transactions on internet technology [online], 17(3), article 24. Available from: https://doi.org/10.1145/3007210

• Journal Article Type: Article
• Acceptance Date: Oct 31, 2016
• Online Publication Date: Jun 12, 2017
• Publication Date: Aug 31, 2017
• Deposit Date: May 2, 2022
• Publicly Available Date: May 2, 2022
• Journal: ACM Transactions on Internet Technology
• Print ISSN: 1533-5399
• Electronic ISSN: 1557-6051
• Publisher: Association for Computing Machinery (ACM)
• Peer Reviewed: Peer Reviewed
• Volume: 17
• Issue: 3
• Article Number: 24
• DOI: https://doi.org/10.1145/3007210
• Keywords: Debating technology; Argument; Argumentation; Dialogue; Sensemaking; Engagement; Analytic
• Public URL: https://rgu-repository.worktribe.com/output/1580657