Detecting, Understanding & Mitigating Russian Online Propaganda with Machine Learning

• Applicant: Professor Dr. Stefan Feuerriegel
• Subject Area: Data Management, Data-Intensive Systems, Computer Science Methods in Business Informatics
• Term: since 2024
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 543018872

The massive spread of online propaganda has been identified as a major threat to democracies due to its widespread use in modern warfare to undermine trust and manipulate people’s opinions. This is alarming, especially since Russia has launched large-scale online campaigns to manipulate public opinion in the European Union and across the world. Our project aims to detect, understand, and mitigate the spread of Russian online propaganda. Thereby, this project fills important gaps in the literature: How can online propaganda be detected and mitigated with machine learning tools? What dissemination strategies are leveraged by propaganda campaigns to promote online diffusion? What behavioral interventions (e.g., debunking, counterspeech) are effective in curbing the spread of online propaganda at scale? Thereby, we will identify characteristics that are unique to the spreading of online propaganda and thus its mitigation. Our project has a unique focus on developing new machine learning approaches to enable theory building and effective countermeasures. Specifically, we develop new machine learning approaches to detect online propaganda. Further, we adapt causal machine learning to design personalized countermeasures aimed at curbing the spread of online propaganda. As a result, we provide a principled, evidence-based toolbox to curb online propaganda at scale.

• DFG Programme: Research Grants