{"title":"No Place For Hate Speech @ AMI: Convolutional Neural Network and Word Embedding for the Identification of Misogyny in Italian (short paper)","authors":"Adriano dos S. R. da Silva, N. T. Roman","doi":"10.4000/books.aaccademia.6834","DOIUrl":null,"url":null,"abstract":"English. In this article, we describe two classification models (a Convolutional Neural Network and a Logistic Regression classifier), arranged according to three different strategies, submitted to subtask A of Automatic Misogyny Identification at EVALITA 2020. Results were very encouraging for detecting misogyny, even though aggressiveness was less accurate. Our second strategy, consisting of a Convolutional Neural Network and logistic regression to identify misogyny and aggressiveness, respectively, won the sixth place in the competition. Italiano. In questo articolo, descriviamo due modelli di classificazione (i.e., Convolutional Neural Network e Regressione Logistica), organizzati secondo tre diverse strategie, per il subtask A dello shared task Automatic Misogyny Identification a EVALITA 2020. I risultati sono stati molto incoraggianti nel rilevamento della misoginia, anche se l’aggressività viene riconosciuta con una precisione più basse. La nostra seconda strategia (Convolutional Neural Network per misoginia e Regressione Logistica per aggressività) ci ha permesso di ottenere il sesto posto","PeriodicalId":184564,"journal":{"name":"EVALITA Evaluation of NLP and Speech Tools for Italian - December 17th, 2020","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"EVALITA Evaluation of NLP and Speech Tools for Italian - December 17th, 2020","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4000/books.aaccademia.6834","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
English. In this article, we describe two classification models (a Convolutional Neural Network and a Logistic Regression classifier), arranged according to three different strategies, submitted to subtask A of Automatic Misogyny Identification at EVALITA 2020. Results were very encouraging for detecting misogyny, even though aggressiveness was less accurate. Our second strategy, consisting of a Convolutional Neural Network and logistic regression to identify misogyny and aggressiveness, respectively, won the sixth place in the competition. Italiano. In questo articolo, descriviamo due modelli di classificazione (i.e., Convolutional Neural Network e Regressione Logistica), organizzati secondo tre diverse strategie, per il subtask A dello shared task Automatic Misogyny Identification a EVALITA 2020. I risultati sono stati molto incoraggianti nel rilevamento della misoginia, anche se l’aggressività viene riconosciuta con una precisione più basse. La nostra seconda strategia (Convolutional Neural Network per misoginia e Regressione Logistica per aggressività) ci ha permesso di ottenere il sesto posto