Document Type

Conference Proceeding

Publication Date


Publication Title

The 16th International AAAI Conference on Web and Social Media (ICWSM), Atlanta, GA, USA, 2022

Publisher Name

Association for the Advancement of Artificial Intelligence


As online communication continues to become more prevalent, instances of cyberbullying have also become more common, particularly on social media sites. Previous research in this area has studied cyberbullying outcomes, predictors of cyberbullying victimization/perpetration, and computational detection models that rely on labeled datasets to identify the underlying patterns. However, there is a dearth of work examining the content of what is said when cyberbullying occurs and most of the available datasets include only basic labels (cyberbullying or not). This paper presents an annotated Instagram dataset with detailed labels about key cyberbullying properties, such as the content type, purpose, directionality, and co-occurrence with other phenomena, as well as demographic information about the individuals who performed the annotations. Additionally, results of an exploratory logistic regression analysis are reported to illustrate how new insights about cyberbullying and its automatic detection can be gained from this labeled dataset.


Author Posting. Copyright © 2021, Association for the Advancement of Artificial Intelligence. This is the author's version of the work. It is posted here for personal use, not for redistribution. The definitive version will be published in Proceedings of the Sixteenth International AAAI Conference on Web and Social Media.