UniBO @ AMI: A Multi-Class Approach to Misogyny and Aggressiveness Identification on Twitter Posts Using AlBERTo

We describe our participation in the EVALITA 2020 (Basile et al., 2020) shared task on Automatic Misogyny Identification. We focus on task A —Misogyny and Aggressive Behaviour Identification— which aims at detecting whether a tweet in Italian is misogynous and, if so, whether it is aggressive. Rather than building two different models, one for misogyny and one for aggressiveness identification, we handle the problem as one single multi-label classification task, considering three classes: non-misogynous, non-aggressive misogynous, and aggressive misogynous. Our three-class supervised model, built on top of AlBERTo, obtains an overall F1 score of 0.7438 on the task test set (F1 = 0.8102 for the misogyny and F1 = 0.6774 for the aggressiveness task), which outperforms the top submitted model (F1 = 0.7406)

A Corpus for Sentence-level Subjectivity Detection on English News Articles

We present a novel corpus for subjectivity detection at the sentence level. We develop new annotation guidelines for the task, which are not limited to language-specific cues, and apply them to produce a new corpus in English. The corpus consists of 411 subjective and 638 objective sentences extracted from ongoing coverage of political affairs from online news outlets. This new resource paves the way for the development of models for subjectivity detection in English and across other languages, without relying on language-specific tools like lexicons or machine translation. We evaluate state-of-the-art multilingual transformer-based models on the task, both in mono- and cross-lingual settings, the latter with a similar existing corpus in Italian language. We observe that enriching our corpus with resources in other languages improves the results on the task

EVALITA Evaluation of NLP and Speech Tools for Italian - December 17th, 2020

Welcome to EVALITA 2020! EVALITA is the evaluation campaign of Natural Language Processing and Speech Tools for Italian. EVALITA is an initiative of the Italian Association for Computational Linguistics (AILC, http://www.ai-lc.it) and it is endorsed by the Italian Association for Artificial Intelligence (AIxIA, http://www.aixia.it) and the Italian Association for Speech Sciences (AISV, http://www.aisv.it)

MBN 2016 Aesthetic Breast Meeting BIA-ALCL Consensus Conference Report

reast implant-associated anaplastic large cell lymphoma (BIA-ALCL) is an uncommon neoplasia occurring in women with either cosmetic or reconstructive breast implants. The actual knowledge about BIA-ALCL deriving from the literature presents several limits, and it remains difficult to make inferences about BIA-ALCL epidemiology, cause, and pathogenesis. This is the reason why the authors decided to organize an evidence-based consensus conference during the Maurizio Bruno Nava (MBN 2016) Aesthetic Breast Meeting held in Milan in December of 2016. Twenty key opinion leaders in the field of plastic surgery from all over the world have been invited to express and discuss their opinion about some key questions on BIA-ALCL, trying to reach a consensus about BIA-ALCL cause, pathogenesis, diagnosis, and treatment in light of the actual best evidence. Copyright © 2017 by the American Society of Plastic Surgeons