With the increasing number of smart device users, data transmission between users is becoming more important, and a network architecture called opportunistic mobile social network (OMSN) is gaining attention. However, routing in OMSNs is a challenging problem due to the frequent disconnection between nodes and the absence of paths from the source to the destination. It results in a complex topology and a low packet transmission success rate. Therefore, we propose a novel routing algorithm called the temporal social interactions-based routing protocol (TSIRP) for solving the problem of low network performance due to the improper selection of message relay nodes. First, we focus on the temporal context of social interactions. Specifically, at a certain time of the day, a person has specific people with whom the person usually interacts (e.g., workers usually meet co-workers during working hours; students usually meet their classmates during class). Based on temporal social interactions between nodes, potential forwarding metrics are proposed and calculated for each time of the day to make forwarding decisions. Second, we propose a new scheme to control the message spreading rate, which allows achieving a balance between delivery latency and overhead ratio. In addition, an analytical model is also designed using an absorbing Markov chain to estimate the performance of TSIRP. Simulations were also conducted, and the results indicate that TSIRP can achieve better performance than existing routing protocols in terms of packet delivery ratio, delivery latency, network overhead ratio, and average hop count.INDEX TERMS Forwarding token, opportunistic mobile social network, potential forwarding metric, spreading rate control value.