Abstract Social Internet of Things (SIoT) integrates the social network with the Internet of Things (IoT) and has become a hot research issue for its potential to support novel IoT applications and networking services in more effective and efficient ways. The search engine, which is primarily designed for social network users to acquire interested information, also plays an important role in SIoT. There even exist search engines specially designed for SIoT. Using a search engine, people can easily find the smart devices in SIoT. Specifically, a search engine assists the information dissemination, i.e., enabling users (both humans and things) to access interested objects (both humans and things) with keywords-searching and transferring contents from the source directly to potential interested users. Accompanying such processes, the SIoT evolves as new links emerge between users and their interested objects. In this paper, we aim to quantitatively characterize how a search engine influences the social relationship in the IoT. Firstly, we point out that the search engine serves as the medium between the social network and the IoT, and then we propose a Search Social Internet of Things (SSIoT) model for SIoT evolution. Secondly, we adopt six performance metrics, namely, degree distribution, network diameter, average distance, network density, network stability, and user betweenness. Theoretically, we prove that the degree distribution follows an intensified power-law, the network diameter and the average distance shrink, network density, network stability, and user betweenness are greater in SSIoTs. Thirdly, we quantitatively show that a search engine accelerates malicious code propagation in SIoTs. Finally, based on four real-world data sets (i.e., CDBLP, Facebook, Weibo, and P2P), we verify our theoretical findings.