My name is John Lawrence and I am a researcher with the
Centre for Argument Technology at the University of Dundee.

My research focuses include: argument mining, argument representation and computational linguistics.

You can read more about me, view my publications and projects I have worked on.

Featured Projects

OVA: Online Visualisation of Argument



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Recent Publications

Lakatos-style collaborative mathematics through dialectical, structured and abstract argumentation

Pease, A., Lawrence, J., Budzynska, K., Corneli, J., & Reed, C. (2017)

Artificial Intelligence


The simulation of mathematical reasoning has been a driving force throughout the history of Artificial Intelligence research. However, despite significant successes in computer mathematics, computers are not widely used by mathematicians apart from their quotidian applications. An oft-cited reason for this is that current computational systems cannot do mathematics in the way that humans do. We draw on two areas in which Automated Theorem Proving (ATP) is currently unlike human mathematics: firstly in a focus on soundness, rather than understandability of proof, and secondly in social aspects. Employing techniques and tools from argumentation to build a framework for mixed-initiative collaboration, we develop three complementary arcs.

Multi-level computational methods for interdisciplinary research in the HathiTrust Digital Library

Murdock et al. (2017)



We show how faceted search using a combination of traditional classification systems and mixed-membership topic models can go beyond keyword search to inform resource discovery, hypothesis formulation, and argument extraction for interdisciplinary research. Our test domain is the history and philosophy of scientific work on animal mind and cognition. The methods can be generalized to other research areas and ultimately support a system for semi-automatic identification of argument structures. We provide a case study for the application of the methods to the problem of identifying and extracting arguments about anthropomorphism during a critical period in the development of comparative psychology.

Using Argumentative Structure to Interpret Debates in Online Deliberative Democracy and eRulemaking

Lawrence, J., Park, J., Budzynska, K., Cardie, C., Konat, B., and Reed, C. (2017)

ACM Transactions on Internet Technology


Governments around the world are increasingly utilising online platforms and social media to engage with, and ascertain the opinions of, their citizens. Whilst policy makers could potentially benefit from such enormous feedback from society, they first face the challenge of making sense out of the large volumes of data produced. In this article, we show how the analysis of argumentative and dialogical structures allows for the principled identification of those issues that are central, controversial, or popular in an online corpus of debates. Although areas such as controversy mining work towards identifying issues that are a source of disagreement, by looking at the deeper argumentative structure, we show that a much richer understanding can be obtained. We provide results from using a pipeline of argument-mining techniques on the debate corpus, showing that the accuracy obtained is sufficient to automatically identify those issues that are key to the discussion, attracting proportionately more support than others, and those that are divisive, attracting proportionately more conflicting viewpoints.

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