Cyberbullying detection through deep learning: A case study of Turkish celebrities on Twitter

Article type: Research Article

Authors: Karadağ, Bulut^{a; *} | Akbulut, Akhan^b | Zaim, Abdul Halim^a

Affiliations: [a] Department of Computer Engineering, Istanbul Commerce University, Istanbul, Turkey | [b] Department of Computer Engineering, Istanbul Kültür University, Istanbul, Turkey

Correspondence: [*] Corresponding author. E-mail: [email protected].

Abstract: One of the ways that celebs maintain their fame in the modern era is by posting updates and photos to social media platforms like Twitter, Instagram, and Facebook. Comments left on their posts, however, expose them to cyberbullying. Cyberbullying, as a form of electronic device-based harassment, negatively impacts the lives of individuals. Thirty famous people from the fields of acting, art, music, politics, sports, and writing were chosen for this research. These notable figures include the top five Twitter followers of Turkey in each demographic. Between December 2019 and December 2020, comment responses for each celebrity were collated. Using the Deep Learning model, we were able to detect abuse content with an accuracy of 89%. Additionally, the percentage of celebrities exposed to cyberbullying by group was presented.

Keywords: Cyberbullying, deep learning, Twitter, long short-term memory, social media analysis

DOI: 10.3233/WEB-221805

Journal: Web Intelligence, vol. 21, no. 1, pp. 61-70, 2023