With this demonstration we introduce AFAlpha, a prototype of an Argument Mining tool, working in unison with Quaestio-it, an online social debating platform. While AFAlpha extracts arguments from text, as well as attack and support relations between arguments, Quaestio-it is concerned with visualising and evaluating interactive debates. We thus use Quaestio-it to represent and visualise output ...

This research aims to analyse the evolution of "online epistemic communities" (OECs), focussing on the collective processes of article elaboration in Wikipedia. It responds to the important yet still open challenge in Cognitive Ergonomics of constructing methods for analysing/ensuring the quality of collective products, in relation to both their intrinsic characteristics (e.g. completeness, rea...

People taking part in argumentativedebates through collective annotations face a highly cognitive taskwhen trying to estimate the group’s global opinion. In order to reduce this effort, we propose in this paper to model such debates prior to evaluating their “social validation.” Computing the degree of global confirmation (resp. refutation) enables the identification of consensual (resp. contro...

Social-media data provides increasing opportunities for automated analysis of large sets of textual documents. So far, automated tools have been developed to account for either the social networks between the participants of the debates, or to analyze the content of those debates. Less attention has been paid to mapping co-occurring actors (participants) and topics (content) in online debates t...

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This paper proposes a new task in argument mining in online debates. The task includes three annotations steps that result in fine-grained annotations of agreement and disagreement at a propositional level. We report on the results of a pilot annotation task on identifying sentences that are directly addressed in the comment.

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