SemEval 2019

AbstractIn a world of information operations, influence campaigns, and fake news, classification of news articles as following hyperpartisan argumentation or not is becoming increasingly important. We present a deep learning-based …...

AbstractThis paper describes a novel research approach to detect type and target of offensive posts in social media using a capsule network. The input to the network was character embeddings …...

AbstractThis paper addresses the problem of modeling textual conversations and detecting emotions. Our proposed model makes use of 1) deep transfer learning rather than the classical shallow methods of word …...

AbstractThis paper summarizes the participation of Stop PropagHate team at SemEval 2019. Our approach is based on replicating one of the most relevant works on the literature, using word embeddings …...

AbstractThis paper reports an experiment carried out to investigate the relevance of several syntactic, stylistic and pragmatic features on the task of distinguishing between mainstream and partisan news articles. The …...