MDD @ AMI: Vanilla Classifiers for Misogyny Identification
Samer El Abassi, Sergiu Nisioi · Accademia University Press eBooks · 2020
In this report1, we present a set of vanilla classifiers that we used to identify misogynous and aggressive texts in Italian social media. Our analysis shows that simple classifiers with little feature engineering have a strong tendency to overfit and yield a strong bias on the test set. Additionally, we investigate the usefulness of function words, pronouns, and shallow-syntactical features to observe whether misogynous or aggressive texts have specific stylistic elements.