Am I Being Bullied on Social Media? An Ensemble Approach to Categorize Cyberbullying
2021 IEEE International Conference on Big Data, Big Data 2021
; : 2442-2453, 2021.
Article
in English
| Scopus | ID: covidwho-1730869
ABSTRACT
People can easily reveal their aggressive remarks on social media platforms using the anonymity it provides. During the COVID-19 pandemic, the usage of social media has been increased several times according to surveys and people are vulnerable to cyber attacks now more than ever. Prevention of cyberbullying needs careful monitoring and identification. Most of the existing works on cyberbullying detection employed traditional machine learning classifiers with handcrafted fea-tures, and deep learning-based models have made their way in this domain very recently. Categorizing cyberbullying based on traits is a complex task and needs contextual consideration. In this work, we have proposed a new approach to detect cyberbullying on social media platforms using a neural ensemble method of transformer-based architectures with attention mechanism. Our proposed architecture is trained on one balanced and one imbalanced dataset and outperforms the given ML and DNN baselines by a significant margin in both cases. We achieved an average F1-score of 95.59% for five classes and 90.65% for six classes on the Fine-Grained Cyberbullying Dataset (FGCD), and 87.28% on Twitter parsed dataset. Our in-depth results provide great insights into the effectiveness of transformer-based models in cyberbullying detection and paves the way for future researches to combat this serious online issue. We have released our models and code.1 © 2021 IEEE.
Cyberbullying Detection; Ensemble Learning; Natural Language Processing; Social Media Data Mining; Transformers; Computer crime; Deep learning; Learning algorithms; Network security; Social networking (online); Complex task; Cyber bullying; Ensemble approaches; Learning Based Models; Social media; Social media data minings; Social media platforms; Transformer; Natural language processing systems
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Language:
English
Journal:
2021 IEEE International Conference on Big Data, Big Data 2021
Year:
2021
Document Type:
Article
Similar
MEDLINE
...
LILACS
LIS