One of our main research interests is Argument Mining (AM). It can be informally described as the problem of automatically detecting and extracting arguments from the text. Arguments are usually represented as a combination of a premise (a fact) that supports a subjective conclusion (opinion, claim). Argumentation Mining touches a wide variety of well-known NLP tasks, spanning from sentiment analysis, stance detection to summarization and dialogue systems.
Apply argumentative reasoning to hate speech to make implicit content explicit
Make use of speech information (e.g. prosody) to enhance the set of features that can be used to detect arguments.