Social Diffusion Sources Can Escape Detection

Abstract

Influencing (and being influenced by) others through social networks is fundamental to all human societies. Whether this happens through the diffusion of rumors, opinions, or viruses, identifying the diffusion source (i.e., the person that initiated it) is a problem that has attracted much research interest. Nevertheless, existing literature has ignored the possibility that the source might strategically modify the network structure (by rewiring links or introducing fake nodes) to escape detection. Here, without restricting our analysis to any particular diffusion scenario, we close this gap by evaluating two mechanisms that hide the source-one stemming from the source's actions, the other from the network structure itself. This reveals that sources can easily escape detection, and that removing links is far more effective than introducing fake nodes. Thus, efforts should focus on exposing concealed ties rather than planted entities; such exposure would drastically improve our chances of detecting the diffusion source.

100 pages, 80 figures

References in corpus (5)

• Information dynamics shape the networks of Internet-mediated prostitution
• Reconstructing propagation networks with natural diversity and identifying hidden sources
• Identification of Patient Zero in Static and Temporal Networks - Robustness and Limitations
• Finding Patient Zero: Learning Contagion Source with Graph Neural Networks
• Back to the Past: Source Identification in Diffusion Networks from Partially Observed Cascades