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Along with the convenience brought by the open social media platforms for the users, there are also many security and trustworthiness problems like malicious websites, information cheating and lack of trust. Security and trustworthiness of social platforms, as the foundation of social interactions, play an important role in information sharing and communication. The traditional evaluations of security and trust are only focused on trust relationship among users and security implementation, however the evaluation and measurement for social platforms have not yet been well done. Therefore a novel method to evaluate the security and trust of the online social network platforms based on signaling theory in information management science is proposed. Firstly, we classified the signals of security and trust of the generic OSNs platform itself, and formalized static attributes and dynamic behaviors features with the OWL and the temporal logic. Then, a FAHP holistic evaluation was made to confirm signals’ indicators weight, and a comprehensive security and trust evaluation computation model was presented by adopting the idea of crowd computing. Finally, an evaluation experiment was carried out on a real multimedia social network platform called CyVOD.net. The experimental results denote that the proposed approach can accurately gain the assessment values of each security and trust element of social platforms, and give effetive guidances for functional evolutions and edition updates for social media platforms.