Johannes Daxenberger
Publications33
Citations327
Highly Influential Citations42
- Publications
- Influence
We investigate neural techniques for end-to-end computational argumentation mining (AM). We frame AM both as a token-based dependency parsing and as a token-based sequence tagging problem, including… Continue Reading
In this paper, we analyze a novel set of features for the task of automatic edit category classification. Edit category classification assigns categories such as spelling error correction, paraphrase… Continue Reading
Increasingly, new forms of organizing for knowledge production are built around self-organizing coproduction community models with ambiguous role definitions. Current theories struggle to explain how… Continue Reading
In this paper, we present a study of the collaborative writing process in Wikipedia. Our work is based on a corpus of 1,995 edits obtained from 891 article revisions in the English Wikipedia. We… Continue Reading
Argument mining has become a popular research area in NLP. It typically includes the identification of argumentative components, e.g. claims, as the central component of an argument. We perform a… Continue Reading
We investigate whether and where multi-task learning (MTL) can improve performance on NLP problems related to argumentation mining (AM), in particular argument component identification. Our results… Continue Reading
Research on peer-production suggests that as participants choose what actions to perform, prototypical activity patterns emerge. Recent work characterized these patterns and demonstrated that… Continue Reading
We present DKPro TC, a framework for supervised learning experiments on textual data. The main goal of DKPro TC is to enable researchers to focus on the actual research task behind the learning… Continue Reading
Argument mining is a core technology for enabling argument search in large corpora. However, most current approaches fall short when applied to heterogeneous texts. In this paper, we present an… Continue Reading
We experiment with two recent contextualized word embedding methods (ELMo and BERT) in the context of open-domain argument search. For the first time, we show how to leverage the power of… Continue Reading