In recent years, the rising use of social media has propelled automated
cyberbullying detection into a prominent research domain. However, challenges
persist due to the absence of a standardized definition and universally
accepted datasets. Many researchers now view cyberbullying as a facet of
cyberaggression, encompassing factors like repetition, peer relationships, and
harmful intent in addition to online aggression. Acquiring comprehensive data
reflective of all cyberbullying components from social media networks proves to
be a complex task. This paper provides a description of an extensive
semi-synthetic cyberbullying dataset that incorporates all of the essential
aspects of cyberbullying, including aggression, repetition, peer relationships,
and intent to harm. The method of creating the dataset is succinctly outlined,
and a detailed overview of the publicly accessible dataset is additionally
presented. This accompanying data article provides an in-depth look at the
dataset, increasing transparency and enabling replication. It also aids in a
deeper understanding of the data, supporting broader research use.

本研究提供了一个广泛的半合成网络欺凌数据集的描述，包括网络欺凌的所有关键要素。该数据集的创建方法简洁地概述，并且还提供了详细的公开可访问数据集的概述。这篇伴随数据文章深入探讨了数据集，增加了透明度并支持复制研究。它还有助于更深入地理解数据，支持更广泛的研究使用。