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Deep Learning as a Digital Tool for the Detection and Prevention of Cyberbullying

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

2 Scopus citations

Abstract

The present research aimed to explore the state-of-the-art of deep learning (DL) techniques focused on the automatic detection of offensive behavior on the Internet, a problematic also known as cyberbullying. For this purpose, the most important DL algorithms were analyzed, as well as the studies conducted with them in order to combat cyberbullying. The information presented in this chapter was collected from a bibliographic search through indexed journals and databases such as Scopus, using keywords that included “cyberbullying”, “Deep learning”, “applications” in order to find relevant scientific articles on this topic. As a result of this analysis, it was concluded that DL presents a novel and effective alternative against cyberbullying. Given the current state of this technology, explored in this chapter, it can be stated that it will become an important tool in the future to successfully combat this problem, although there are still some aspects to be improved.

Original languageEnglish
Title of host publicationCombatting Cyberbullying in Digital Media with Artificial Intelligence
PublisherCRC Press
Pages3-17
Number of pages15
ISBN (Electronic)9781003825036
ISBN (Print)9781032491882
DOIs
StatePublished - 1 Jan 2023

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