Argument mining is the automatic identification and extraction of the structure of inference
and reasoning expressed as arguments presented in natural language. Understanding …

Abstract Argumentation mining is a rising subject in the computational linguistics domain
focusing on extracting structured arguments from natural text, often from unstructured or …

Argument mining is the research area aiming at extracting natural language arguments and
their relations from text, with the final goal of providing machine-processable structured data …

Stance detection (StD) aims to detect an author's stance towards a certain topic and has
become a key component in applications like fake news detection, claim validation, or …

Activation functions play a crucial role in neural networks because they are the
nonlinearities which have been attributed to the success story of deep learning. One of the …

The automatic semantic structuring of scientific text allows for more efficient reading of
research articles and is an important indexing step for academic search engines. Sequential …

Peer-review plays a critical role in the scientific writing and publication ecosystem. To
assess the efficiency and efficacy of the reviewing process, one essential element is to …

Claims are the central component of an argument. Detecting claims across different domains
or data sets can often be challenging due to their varying conceptualization. We propose to …

This paper focuses on text-based affective computing for Jopara, a code-switching language
that combines Guarani and Spanish. First, we collected a dataset of tweets primarily written …

Mining an argument structure from text is an important step for tasks such as argument
search and summarization. While studies on argument (ation) mining have proposed …