# Cyberbullying Detection in Social Networks Using Deep Learning Based Models; A Reproducibility Study

arXiv: https://arxiv.org/abs/1812.08046 · HTML: https://mlsanity.com/paper/1812.08046/

## Key facts

- Cited by 14 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Dec 2018.

## Built on by (most cited first, 14 of 14)

- [A Survey on Multimodal Disinformation Detection](https://mlsanity.com/paper/2103.12541/) (2021)
- [Data Expansion using Back Translation and Paraphrasing for Hate Speech Detection](https://mlsanity.com/paper/2106.04681/) (2021)
- [Transfer Language Selection for Zero-Shot Cross-Lingual Abusive Language Detection](https://mlsanity.com/paper/2206.00962/) (2022)
- [Cyberbullying Detection for Low-resource Languages and Dialects: Review of the State of the Art](https://mlsanity.com/paper/2308.15745/) (2023)
- [Cyberbullying detection across social media platforms via platform-aware adversarial encoding](https://mlsanity.com/paper/2204.00334/) (2022)
- [Sexism detection: The first corpus in Algerian dialect with a code-switching in Arabic/ French and English](https://mlsanity.com/paper/2104.01443/) (2021)
- [On the reproducibility of fully convolutional neural networks for modeling time-space evolving physical systems](https://mlsanity.com/paper/2105.05482/) (2021)
- [Improving Classifier Training Efficiency for Automatic Cyberbullying Detection with Feature Density](https://mlsanity.com/paper/2111.01689/) (2021)
- [Automated Detection of Doxing on Twitter](https://mlsanity.com/paper/2202.00879/) (2022)
- [Detecting LGBTQ+ Instances of Cyberbullying](https://mlsanity.com/paper/2409.12263/) (2024)
- [Identifying Cyberbullying Roles in Social Media](https://mlsanity.com/paper/2412.16417/) (2024)
- [Securing Social Spaces: Harnessing Deep Learning to Eradicate Cyberbullying](https://mlsanity.com/paper/2404.03686/) (2024)
- [A multilingual dataset for offensive language and hate speech detection for hausa, yoruba and igbo languages](https://mlsanity.com/paper/2406.02169/) (2024)
- [Detection of Cyberbullying in GIF using AI](https://mlsanity.com/paper/2512.07838/) (2025)

## Abstract (arXiv)

Cyberbullying is a disturbing online misbehaviour with troubling consequences. It appears in different forms, and in most of the social networks, it is in textual format. Automatic detection of such incidents requires intelligent systems. Most of the existing studies have approached this problem with conventional machine learning models and the majority of the developed models in these studies are adaptable to a single social network at a time. In recent studies, deep learning based models have found their way in the detection of cyberbullying incidents, claiming that they can overcome the limitations of the conventional models, and improve the detection performance. In this paper, we investigate the findings of a recent literature in this regard. We successfully reproduced the findings of this literature and validated their findings using the same datasets, namely Wikipedia, Twitter, and Formspring, used by the authors. Then we expanded our work by applying the developed methods on a new YouTube dataset (~54k posts by ~4k users) and investigated the performance of the models in new social media platforms. We also transferred and evaluated the performance of the models trained on one platform to another platform. Our findings show that the deep learning based models outperform the machine learning models previously applied to the same YouTube dataset. We believe that the deep learning based models can also benefit from integrating other sources of information and looking into the impact of profile information of the users in social networks.