nlp

What the [MASK]? Making Sense of Language-Specific BERT Models

Recently, Natural Language Processing (NLP) has witnessed an impressive progress in many areas, due to the advent of novel, pretrained contextual representation models. In particular, Devlin et al. (2019) proposed a model, called BERT (Bidirectional …

CAGE: Constrained deep Attributed Graph Embedding

In this paper we deal with complex attributed graphs which can exhibit rich connectivity patterns and whose nodes are often associated with attributes, such as text or images. In order to analyze these graphs, the primary challenge is to find an …

Hate Speech and Misogyny Detection

How fair Machine Learning models could solve Hate Speech and Misogyny Detection?

MONICA

MONItoring Coverage, Attitudes and Accessibility of Italian measures in response to COVID-19

Unintended Bias in Misogyny Detection

During the last years, the phenomenon of **hate against women** increased exponentially especially in online environments such as microblogs. Although this alarming phenomenon has triggered many studies both from computational linguistic and machine …

Word Embeddings for Unsupervised Named Entity Linking

The huge amount of textual user-generated content on the Web has incredibly grown in the last decade, creating new relevant opportunities for different real-world applications and domains. In particular, microblogging platforms enables the collection …

SemEval-2019 Task 5: Multilingual Detection of Hate Speech Against Immigrants and Women in Twitter

The paper describes the organization of the SemEval 2019 Task 5 about the detection of **hate speech against immigrants and women** in **Spanish and English** messages extracted from Twitter. The task is organized in two related classification …