###### Abstract  
With the popularization of mobile communication equipment, human activities have an increasing impact on the structure of networks, and so the social characteristics of opportunistic networks become increasingly obvious. Opportunistic networks are increasingly used in social situations. However, existing routing algorithms are not suitable for opportunistic social networks, because traditional opportunistic network routing does not consider participation in human activities, which usually causes a high ratio of transmission delay and routing overhead. Therefore, this research proposes an effective data transmission algorithm based on social relationships (ESR), which considers the community characteristics of opportunistic mobile social networks. This work uses the idea of the action to divide the nodes in the network into communities, reduces the number of inefficient nodes in the community, and performs another contraction of the structure. Simulation results show that the ESR algorithm, through community transmission, is not only faster and safer, but also has lower transmission delay and routing overhead compared with the spray and wait algorithm, SCR algorithm and the EMIST algorithm. opportunistic networks; opportunistic mobile social networks; community division; community structure contraction +
Footnote †: journal:  
0000-0001-5000-0000-00001-5000]J. Xu  
0000-0001-5000-0000-00001-5000]X. Xu  
0000-0001-5000-0000-00001-50000-00001-50000-00001-50000-00001-500000-00001-5000001-  
as the \"storage-carry-and-forward\" mechanism, which is the basic principle of data transmission and routing in opportunistic networks [7]. In the real world, people wear mobile phones, movement bracelets and smart watches which have mobile communication functions. The mobile terminals each person carries have a communication range within which information can be transmitted directly. However, because people are in motion constantly, the target node is not necessarily within the communication range of the current node. In this case, the node will keep information about the data, carry the data during movement, and pass the information to the node it thinks can contact the target node during the continuous movement. With the advent of the era of big data and 5G, the amount of data that needs to be transmitted in the communication process has become very large, and social networks can no longer meet the demands of communication. We refer to this kind of opportunistic network in social network research as an opportunistic social network, which has both the social attributes of social networks and the data transmission characteristics of opportunistic networks. In this scenario, the routing needs \"opportunity\" for forwarding, e.g., people contacting each other by chance using mobile wireless devices, and here opportunistic social networks demonstrate their unique applicability. The message forwarding mechanism of opportunistic social networks does not require a stable end-to-end connection. Instead, we can choose the most appropriate node in the network structure to transmit information through. This means that an opportunistic network can also be established between strangers, where if the appropriate node appears, the information can be transferred. In other words, if people use Bluetooth or public Wi-Fi within a communication range, they can use the opportunistic social network to deliver messages. If there is no suitable node in the current communication range, the current node can save the information to the cache and wait to find an \"opportunity\" to transfer the information during movement. As human beings take part in networked activities, the behavior of mobile nodes shows certain social features [8]. With the rapid popularization of portable mobile devices which have short distance communication functions, ever more users exploit these portable devices to contact and share data between each other.