Harnessing Inter-Organizational Collaboration and Automation to Combat Online Hate Speech: A Qualitative Study with German Reporting Centers

In Germany and other countries, specialized non-profit reporting centers combat online hate speech by submitting criminal content to law enforcement agencies, forwarding deletion requests to social media platforms, and providing counseling to victims, thus contributing to the governance mechanism of content moderation as intermediaries between victims and various organizations. Whereas research in computer-supported cooperative work has extensively explored collaboration of and automation for content moderators, there are no works that focus on reporting centers. Based on expert interviews with their staff (N=15), this study finds that most German centers share a collaborative workflow, of which multiple tasks are heavily dependent on inter-organizational exchange. However, there are differences in their implementation of monitoring, content assessment, automation technology adoption, and external collaborators. As the centers are faced with diverse challenges, such as borderline case assessment, psychological burdens, limited visibility, conflicting goals with other actors, and manual repetitive work, our study contributes with nine implications for designing and researching supportive technologies. They provide suggestions for improving hate speech gathering and reporting, researching hate speech prioritization and assessment algorithms, and designing case processing systems. Beyond that, we outline directions for research on inter-organizational collaboration.