In this paper, we design a friendly jammer selection scheme for the social Internet of Things (IoT). A typical social IoT is composed of a cellular network with underlaying Device-to-Device (D2D) communications. In our scheme, we consider signal characteristics over a physical layer and social attribute information of an application layer simultaneously. Using signal characteristics, one of the D2D gadgets is selected as a friendly jammer to improve the secrecy performance of a cellular device. In return, the selected D2D gadget is allowed to reuse spectrum resources of the cellular device. Using social relationship, we analyze and quantify the social intimacy degree among the nodes in IoT to design an adaptive communication time threshold. Applying an artificial intelligence forecasting model, we further forecast and update the intimacy degree, and then screen and filter potential devices to effectively reduce the detection and calculation costs. Finally, we propose an optimal scheme to integrate the virtual social relationship with actual communication systems. To select the optimal D2D gadget as a friendly jammer, we apply Kuhn-Munkres (KM) algorithm to solve the maximization problem of social intimacy and cooperative jamming. Comprehensive numerical results are presented to validate the performance of our scheme.