In this paper we consider the insights that can be gained by considering large scale argument networks and the complex interactions between their constituent propositions. We investigate metrics for analysing properties of these networks, illustrating these using a corpus of arguments taken from the 2016 US Presidential Debates. We present techniques for determining these features directly from...

In this research, we deployed an automated fact-checking system (ClaimBuster) on the 2016 presidential primary debates and assessed its performance compared to professional news organizations. In real-time, ClaimBuster scored the statements made by candidates on check-worthiness, the likelihood that the statement contained an important factual claim. Its discrimination compared to professional ...

In this paper, we investigate how topic dynamics during the course of an interaction correlate with the power differences between its participants. We perform this study on the US presidential debates and show that a candidate’s power, modeled after their poll scores, affects how often he/she attempts to shift topics and whether he/she succeeds. We ensure the validity of topic shifts by confirm...

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In this paper, we present Lexical Episode Plots, a novel automated text-mining and visual analytics approach for exploratory text analysis. In particular, we first describe an algorithm for automatically annotating text regions to examine prominent themes within natural language texts. The algorithm is based on lexical chaining to find spans of text in which the frequency of a term is significa...