Argument Analytics

Rapid growth in the area of argument mining has resulted in an ever increasing volume of analysed argument data. Being able to store information about arguments people make in favour or against different opinions, decisions and actions is a highly valuable resource, yet extremely challenging for sense-making. How, for example, can an analyst quickly check whether in a corpus of citizen dialogue people tend to rather agree or disagree with new policies proposed by the department of transportation; how can she get an insight into the interactions typical of this specific dialogical context; how can the general public easily see which presidential candidate is currently winning the debate by being able to successfully defend his arguments? In this paper, we propose Argument Analytics – a suite of techniques which provide interpretation of, and insight into, large-scale argument data for both specialist and general audiences

Mining Ethos in Political Debate

Despite the fact it has been recognised since Aristotle that ethos and credibility play a critical role in many types of communication, these facts are rarely studied in linguistically oriented AI which has enjoyed such success in processing complex features as sentiment, opinion, and most recently arguments. This paper shows how a text analysis pipeline of structural and statistical approaches to natural language processing (NLP) can be deployed to tackle ethos by mining linguistic resources from the political domain. We summarise a coding scheme for annotating ethotic expressions; present the first openly available corpus to support further, comparative research in the area; and report results from a system for automatically recognising the presence and polarity of ethotic expressions. Finally, we hypothesise that in the political sphere, ethos analytics – including recognising who trusts whom and who is attacking whose reputation – might act as a powerful toolset for understanding and even anticipating the dynamics of governments. By exploring several examples of correspondence between ethos analytics in political discourse and major events and dynamics in the political landscape, we uncover tantalising evidence in support of this hypothesis

Intertextual correspondence for integrating corpora

We present intertextual correspondence (ITC) as an integrative technique for combining annotated text corpora. The topical correspondence between different texts can be exploited to establish new annotation connections between existing corpora. Although the general idea should not be restricted to one particular theoretical framework, we explain how the annotation of intertextual correspondence works for two corpora annotated with argumentative notions on the basis of Inference Anchoring Theory. The annotated corpora we take as examples are topically and temporally related: the first corpus comprises television debates leading up to the 2016 presidential elections in the United States, the second corpus consists of commentary on and discussion of those debates on the social media platform Reddit. The integrative combination enriches the existing corpora in terms of the argumentative density, conceived of as the number of inference, conflict and rephrase relations relative to the word count of the (sub-)corpus. ITC also affects the global properties of the corpus, such as the most divisive issue. Moreover, the ability to extend existing corpora whilst maintaining the level of internal cohesion is beneficial to the use of the integrated corpus as resource for text and argument mining based on machine learning.</p

The argument web:an online ecosystem of tools, systems and services for argumentation

The Argument Web is maturing as both a platform built upon a synthesis of many contemporary theories of argumentation in philosophy and also as an ecosystem in which various applications and application components are contributed by different research groups around the world. It already hosts the largest publicly accessible corpora of argumentation, and has the largest number of interoperable and cross compatible tools for the analysis, navigation and evaluation of arguments across a broad range of domains, languages and activity types. Such interoperability is key in allowing innovative combinations of tool and data reuse that can further catalyse the development of the field of computational argumentation. The aim of this paper is to summarise the key foundations, the recent advances and the goals of the Argument Web, with a particular focus on demonstrating the relevance to, and roots in, philosophical argumentation theory

Argumentation in the 2016 US Presidential Elections:Annotated corpora of television debates and social media reaction

In this paper we present US2016, the largest publicly available set of corpora of annotated dialogical argumentation. The annotation covers argumentative relations, dialogue acts and pragmatic features. The corpora comprise transcriptions of television debates leading up to the 2016 US presidential elections, and reactions to the debates on Reddit. These two constitutive parts of the corpora are integrated by means of the intertextual correspondence between them. The rhetorical richness and high argument density of the communicative context results in cross-genre corpora that are robust resources for the study of the dialogical dynamics of argumentation in three ways: first, in empirical strands of research in discourse analysis and argumentation studies; second, in the burgeoning field of argument mining where automatic techniques require such data; and third, in formulating algorithmic techniques for sensemaking through the development of Argument Analytics

Argument Mining:A Survey

Argument mining is the automatic identification and extraction of the structure of inference and reasoning expressed as arguments presented in natural language. Understanding argumentative structure makes it possible to determine not only what positions people are adopting, but also why they hold the opinions they do, providing valuable insights in domains as diverse as financial market prediction and public relations. This survey explores the techniques that establish the foundations for argument mining, provides a review of recent advances in argument mining techniques, and discusses the challenges faced in automatically extracting a deeper understanding of reasoning expressed in language in general.<br/