## 1 Introduction  
In recent years, due to the rapid development of 5G networks and big data [1], each of us has mobile communication devices, such as smartphones and iPads with Bluetooth, WiFi, etc. These communication devices carried by people have become an integral part of people's daily lives [2]. In this case, we can consider these mobile devices carried or used by people as nodes in opportunistic social networks. Because of the significant sociality of human activities, the movement of nodes conforms to the rules of human social activities, and the strength of the social connection between nodes can often indicate the level of the possibility of an connection opportunity. Consequently, the practicality and effectiveness of opportunistic social network routing protocols can be improved by analyzing the social attributes [3] of nodes. Therefore, combining the opportunistic network [4] with the mobile social network [5; 6] to form the opportunistic social network [7; 8] has both the social characteristics of the social network and the data forwarding characteristics of the opportunistic network, which is a form of the social network's transition to offline materialization. The opportunistic social network adopts a \"storage-carry-forward\" [9; 10] routing model and proposes that data forwarding can be achievedthrough the \"opportunity exchange\" [11; 12; 13] method. This communication relies on the movement of nodes and efficient forwarding algorithms, so that some nodes have the opportunity to act as relay nodes. In other words, the source node needs to find a suitable relay node to send the message to the destination node [14], and this relay node has a great chance to communicate with the source node or the destination node. The message is transmitted and shared in a network that lacks a stable end-to-end connection through this method. It can be seen that in order to improve the efficiency of routing forwarding and reduce the delay, selecting the appropriate relay node is the key to the routing and forwarding algorithm. Recently proposed data forwarding algorithms [15; 16; 17] focus on analyzing social characteristics, including interests, work place, time, social relationships, similarity, etc. Obviously, each social factor may play a different role in the successful data transmission process. In order to select a more suitable relay node, different social attributes need to be selected in different scenarios as a measure of relay node selection. However, the existing algorithms in opportunistic social networks only consider the selection of the best next hop node in a single scenario and do not fully consider the social characteristics of human mobility. The above situation has led to problems such as reducing data forwarding efficiency and greatly increasing the network load, transmission delay, and node energy consumption. In order to solve this problem, it is necessary to find an effective method for selecting the best next hop node under the environment of big data and 5G. There are many excellent strategies for selecting the next hop node in the existing algorithms. Since opportunistic social networks are closely related to social life, another problem arises. This problem is how to integrate human mobility characteristics into complex routing algorithms and propose effective solutions for selecting next hop nodes. Because there are many reasons that cause human movement [18; 19], the behavior of a node has a large number of attributes. Selecting one or more representative attributes as the basis for selecting the next hop node is a solution to existing routing algorithms. Therefore, it is reasonable for different algorithms to choose different attributes in different application scenarios. In real social scenarios, humans move for different reasons at different periods of time. How does one choose the attributes that are suitable for the scenario on the premise of considering the actual motion situation? Finally, choosing the best next hop node according to different attributes is a problem to be solved.