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 t...Show MoreMetadata
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.
Published in: 2019 8th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW)
Date of Conference: 03-06 September 2019
Date Added to IEEE Xplore: 08 December 2019
ISBN Information:
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