🤖 AI Summary
This study addresses the urgent need for systematic strategies to identify malicious actors in online social networks by proposing a structured taxonomy that characterizes their behavioral patterns and roles in disinformation campaigns. Integrating domain expert knowledge with insights from academic literature, the framework delineates the mechanisms through which such actors operate. Developed through qualitative analysis, expert collaboration, and case studies, the taxonomy was validated using social media data centered on anti-immigration discourse. The resulting classification system effectively supports researchers and platform operators in detecting and mitigating disinformation, offering both a theoretical foundation and a practical framework for governance interventions.
📝 Abstract
The broadcast of disinformation in online social networks (OSN) is a growing concern examined across several disciplines, including human-computer interaction (HCI). The pervasive issue has been prompting novel approaches to identify the malicious actors behind the dissemination of deceptive and fabricated content. Analyzing the characteristics and activities of these actors, we designed a taxonomy informed by collaboration with subject matter experts (SMEs) and a review of the academic literature. Our study explores how to distinguish the characteristics, activities, and strategies of malicious actors on OSN and examines how they contribute to the spread of disinformation. We describe the design process and the application of the taxonomy in a case study analyzing anti-migration discourse in social media channels, and reflect on its potential to aid researchers and practitioners in the responsible design of network systems.