Computational Stylometry and Machine Learning for Gender and Age Detection in Cyberbullying Texts
| Title | Computational Stylometry and Machine Learning for Gender and Age Detection in Cyberbullying Texts |
| Publication Type | Conference Paper |
| Year of Publication | 2019 |
| Authors | Pascucci, Antonio, Masucci, Vincenzo, Monti, Johanna |
| Conference Name | 2019 8th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW) |
| ISBN Number | 978-1-7281-3891-6 |
| Keywords | Age Detection, Computational Stylometry, Cyberbullying Detection, feature extraction, Gender Detection, Human Behavior, human factors, Linguistics, machine learning, Metrics, psychology, pubcrawl, Semantics, Social network services, stylometry, Taxonomy |
| 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 collected. |
| URL | https://ieeexplore.ieee.org/document/8925101 |
| DOI | 10.1109/ACIIW.2019.8925101 |
| Citation Key | pascucci_computational_2019 |