Recently, well-prepared and well-crafted fake advertisement campaigns are targeting citizens of the EU as another installment of cyber-crime. Professional criminal groups are mainly targeting young or elderly users of the Internet to steal money or their data, and also deploying malware at their devices. Therefore, to counter such criminal activity, in this paper we propose graph-based approach to analyze and visualize dangerous content. The major contribution of this work is collection of dataset with transcripts of fake campaigns from recent months, and graph-based methods to analyze those criminal campaigns targeted at societies. Experimental results show that the proposed approach enables automated analysis of unstructured text and supports threat intelligence workflows.