Major
Computer Science
Anticipated Graduation Year
2023
Access Type
Open Access
Abstract
Cyberbullying is a widespread form of online harassment with serious negative consequences for victims. In a cyberbullying instance, participants can be classified as harassers, victims, or bystanders. Identifying the roles of participants in cyberbullying instances can facilitate more effective intervention in these instances. We propose a hierarchical attention network to automatically classify the roles of users in cyberbullying conversations on ASKfm, a social media platform where users can ask and answer questions anonymously. Our model combines word, sub-sentence, and sentence-level attention mechanisms to represent the structure of posts on the ASKfm platform and capture relevant features for classification.
Community Partners
Arizona State University
Faculty Mentors & Instructors
Dr. Yasin Silva, Computer Science Department
Supported By
Dr. Deborah Hall, Arizona State University
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License.
Identifying Participant Roles in Cyberbullying Through Hierarchical Attention Networks
Cyberbullying is a widespread form of online harassment with serious negative consequences for victims. In a cyberbullying instance, participants can be classified as harassers, victims, or bystanders. Identifying the roles of participants in cyberbullying instances can facilitate more effective intervention in these instances. We propose a hierarchical attention network to automatically classify the roles of users in cyberbullying conversations on ASKfm, a social media platform where users can ask and answer questions anonymously. Our model combines word, sub-sentence, and sentence-level attention mechanisms to represent the structure of posts on the ASKfm platform and capture relevant features for classification.