Machine and Deep Learning Studies for Cyberbullying Detection

Mümin Ferhat YAKUT, (Gazi Üniversitesi, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü, Ankara, Türkiye)
Cagri Sahin, (Gazi Üniversitesi, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü, Ankara, Türkiye)
Yılmaz ATAY (Gazi Üniversitesi, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü, Ankara, Türkiye)
Savunma Bilimleri Dergisi
8 0
Yıl: 2023 Cilt: 1 Sayı: 43 Sayfa Aralığı: 155 - 177 Metin Dili: İngilizce DOI: 10.17134/khosbd.1087548 İndeks Tarihi: 09-05-2023

Machine and Deep Learning Studies for Cyberbullying Detection

Öz:
The internet revolution in society has various effects on our daily life such as the use of social media. While social media is ubiquitous and great in some aspects, it brings a new issue that appears more and more in today’s world. This new issue, Cyberbullying, involves harming someone by posting or sharing content that causes feelings of embarrassment, guilt, or humiliation. Easily creating fake social media accounts with fake identity further increase cyberbullying incidents and encourages cyberbullies. Cyberbullying can affect people both mentally and physically and can lead to permanent problems. However, studies in this area show that cyberbullying can be prevented. In this study, we review machine learning techniques to detect and prevent cyberbullying, evaluate the performances of the machine and deep learning models, and examine factors that affect the performance of the models. We also discuss the importance of data preprocessing, feature extraction and selection, and classification processes in cyberbullying detection problems.
Anahtar Kelime: Algorithm Classification Cyberbullying Deep Learning Feature Extraction Machine Learning Social Media

Siber Zorbalık Tespiti için Makine Öğrenmesi ve Derin Öğrenme Çalışmaları

Öz:
Toplumdaki internet devrimi, sosyal medya kullanımı gibi günlük hayatımızda çeşitli etkilere sahiptir. Sosyal medya, hayatımızın her alanında kullanılıyor ve bazı alanlarda çok avantajlı olsa da, günümüz dünyasında giderek daha fazla ortaya çıkan yeni bir konuyu da beraberinde getiriyor. Bu yeni konu, Siber Zorbalık, utanç, suçluluk veya aşağılanma duygularına neden olan içerikler göndererek veya paylaşarak birine zarar vermeyi içerir. Sahte kimlikle kolayca sahte sosyal medya hesapları oluşturmak, siber zorbalık olaylarını daha da artırmakta ve siber zorbaları teşvik etmektedir. Siber zorbalık, insanları hem zihinsel hem de fiziksel olarak etkileyebilir ve kalıcı sorunlara yol açabilir. Ancak, bu alanda yapılan çalışmalar siber zorbalığın önlenebilir olduğunu göstermektedir. Bu çalışmada, siber zorbalığı tespit etmek ve önlemek için makine öğrenmesi tekniklerini gözden geçiriyor, makine ve derin öğrenme modellerinin performanslarını değerlendiriyor ve modellerin performansını etkileyen faktörleri inceliyoruz. Ayrıca, siber zorbalık tespitinde veri ön işleme, sınıflandırma, öznitelik çıkarma ve seçme süreçlerinin önemini tartışıyoruz.
Anahtar Kelime: Algoritmalar Derin Öğrenme Makine Öğrenmesi Siber Zorbalık Sosyal Medya

Belge Türü: Makale Makale Türü: Derleme Erişim Türü: Erişime Açık
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APA YAKUT M, Sahin C, ATAY Y (2023). Machine and Deep Learning Studies for Cyberbullying Detection. , 155 - 177. 10.17134/khosbd.1087548
Chicago YAKUT Mümin Ferhat,Sahin Cagri,ATAY YILMAZ Machine and Deep Learning Studies for Cyberbullying Detection. (2023): 155 - 177. 10.17134/khosbd.1087548
MLA YAKUT Mümin Ferhat,Sahin Cagri,ATAY YILMAZ Machine and Deep Learning Studies for Cyberbullying Detection. , 2023, ss.155 - 177. 10.17134/khosbd.1087548
AMA YAKUT M,Sahin C,ATAY Y Machine and Deep Learning Studies for Cyberbullying Detection. . 2023; 155 - 177. 10.17134/khosbd.1087548
Vancouver YAKUT M,Sahin C,ATAY Y Machine and Deep Learning Studies for Cyberbullying Detection. . 2023; 155 - 177. 10.17134/khosbd.1087548
IEEE YAKUT M,Sahin C,ATAY Y "Machine and Deep Learning Studies for Cyberbullying Detection." , ss.155 - 177, 2023. 10.17134/khosbd.1087548
ISNAD YAKUT, Mümin Ferhat vd. "Machine and Deep Learning Studies for Cyberbullying Detection". (2023), 155-177. https://doi.org/10.17134/khosbd.1087548
APA YAKUT M, Sahin C, ATAY Y (2023). Machine and Deep Learning Studies for Cyberbullying Detection. Savunma Bilimleri Dergisi, 1(43), 155 - 177. 10.17134/khosbd.1087548
Chicago YAKUT Mümin Ferhat,Sahin Cagri,ATAY YILMAZ Machine and Deep Learning Studies for Cyberbullying Detection. Savunma Bilimleri Dergisi 1, no.43 (2023): 155 - 177. 10.17134/khosbd.1087548
MLA YAKUT Mümin Ferhat,Sahin Cagri,ATAY YILMAZ Machine and Deep Learning Studies for Cyberbullying Detection. Savunma Bilimleri Dergisi, vol.1, no.43, 2023, ss.155 - 177. 10.17134/khosbd.1087548
AMA YAKUT M,Sahin C,ATAY Y Machine and Deep Learning Studies for Cyberbullying Detection. Savunma Bilimleri Dergisi. 2023; 1(43): 155 - 177. 10.17134/khosbd.1087548
Vancouver YAKUT M,Sahin C,ATAY Y Machine and Deep Learning Studies for Cyberbullying Detection. Savunma Bilimleri Dergisi. 2023; 1(43): 155 - 177. 10.17134/khosbd.1087548
IEEE YAKUT M,Sahin C,ATAY Y "Machine and Deep Learning Studies for Cyberbullying Detection." Savunma Bilimleri Dergisi, 1, ss.155 - 177, 2023. 10.17134/khosbd.1087548
ISNAD YAKUT, Mümin Ferhat vd. "Machine and Deep Learning Studies for Cyberbullying Detection". Savunma Bilimleri Dergisi 1/43 (2023), 155-177. https://doi.org/10.17134/khosbd.1087548
Sayfa Oluşturulma Tarihi
24-04-2024 6:52

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