The aim of this paper is to show the importance of Computational Stylometry (CS) and Machine Learning (ML) support in author’s gender and age detection in cyberbullying texts. We developed a cyberbullying detection platform and we show the results of performances in terms of Precision, Recall and F-Measure for gender and age detection in cyberbullying texts we collected
Computational Stylometry and Machine Learning for Gender and Age Detection in Cyberbullying Texts
Antonio Pascucci;Johanna Monti
2019-01-01
Abstract
The aim of this paper is to show the importance of Computational Stylometry (CS) and Machine Learning (ML) support in author’s gender and age detection in cyberbullying texts. We developed a cyberbullying detection platform and we show the results of performances in terms of Precision, Recall and F-Measure for gender and age detection in cyberbullying texts we collectedFile in questo prodotto:
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