PoliTeam @ AMI: Improving Sentence Embedding Similaritywith Misogyny Lexicons for Automatic Misogyny Identificationin Italian Tweets
Giuseppe Attanasio, Eliana Pastor · Accademia University Press eBooks · 2020
enWe present a multi-agent classification solution for identifying misogynous and aggressive content in Italian tweets. A first agent uses modern Sentence Embedding techniques to encode tweets and a SVM classifier to produce initial labels. A second agent, based on TF-IDF and Misogyny Italian lexicons, is jointly adopted to improve the first agent on uncertain predictions. We evaluate our approach in the Automatic Misogyny Identification Shared Task of the EVALITA 2020 campaign. Results show that TF-IDF and lexicons effectively improve the supervised agent trained on sentence embeddings.