Biblio
Filters: Keyword is Cyberbullying Detection [Clear All Filters]
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2019. Privacy Preserving Cyberbullying Prevention with AI Methods in 5G Networks. 2019 25th Conference of Open Innovations Association (FRUCT). :265—271.
Children and teenagers that have been a victim of bullying can possibly suffer its psychological effects for a lifetime. With the increase of online social media, cyberbullying incidents have been increased as well. In this paper we discuss how we can detect cyberbullying with AI techniques, using term frequency-inverse document frequency. We label messages as benign or bully. We want our method of cyberbullying detection to be privacy-preserving, such that the subscribers' benign messages should not be revealed to the operator. Moreover, the operator labels subscribers as normal, bully and victim. The operator utilizes policy control in 5G networks, to protect victims of cyberbullying from harmful traffic.
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2019. Computational Stylometry and Machine Learning for Gender and Age Detection in Cyberbullying Texts. 2019 8th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW). :1–6.
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.