Research On The Problem Of Maximizing The Impact Of Time Constraints On Polar Social Networks

With the rapid development of Internet and social networking technologies,the emergence of some large-scale social software,such as Wechat,Facebook,Alibaba,etc.,has made people more closely connected through social networks.How to maximize the impact of information dissemination has become Hot issues in recent years.An important issue that needs to be solved to maximize the impact is how to strengthen the connection between users and tap the potential of users to spread information in social networks,so that the spread of social network information is more extensive.In recent years,the problem of maximizing the impact of social networks has been extensively and deeply studied in information diffusion and word-of-mouth marketing.It is mainly to find the most influential seed collections in social networks,through which the information can be spread more widely in social networks.However,most of the research has focused on the problem of maximizing the impact of signed social networks without time constraints.These social networks have both positive and negative information,and are spread without time constraints.However,in real life,some companies often want to spread positive or negative news within a certain period of time,or control the spread of negative news within a certain period of time.This paper refers to this social network as time-constrained.Polar social network.There are many differences between time-constrained polar social networks and ordinary polar social networks.Based on these differences,new propagation models and corresponding new impact maximization algorithms need to be proposed.In view of the above deficiencies and problems,this paper studies from the following two aspects:(1)The effect of time constraints is maximized under the independent cascade model.In order to include the time limit constraint in the process of polar social network propagation,we divide the network into several time trees,and limit the size of each subtree with the constraint of time limit.In the previous impact propagation model,the influence quickly declined to the network area farther away from the source,so most of the calculation was wasted in areas where the impact was small or the impact waszero,especially when the time period was relatively short.Based on this observation,this paper proposes a new calculation method that uses deadline criteria to determine a local graphics area for each node,where the scope of the impact is limited.The method requires a preprocessing step with a small time complexity to divide the social graph into several subtrees,wherein the influence of each node is limited to its subtree region,and then the state of the nodes in each subtree is calculated.The experimental results in the real data set show that the proposed PTIM algorithm has better influence range than other algorithms in the time constraint.(2)The linear threshold model combines the effects of the probability of occurrence to maximize.Although there are many studies that maximize the impact in polar social networks,they are based on the independent symbolic model of the polar symbolic social network.The corresponding research on the maximization algorithm of polar social network influence under linear threshold is also compared.Lacking,this paper proposes the LT-PM model and designs a time-constrained heuristic algorithm on the linear threshold model by calculating the probability of encounters between nodes in the polar social network.The basic idea is to calculate the probability of encountering the function m:E [0,1] for each edge of the social network graph,which is used to measure the probability that the message propagates from a node to its neighbors during the information propagation process,which can more realistically reflect the influence of the social network.process.Finally,experiments on real data sets prove that the proposed algorithm effectively improves the time efficiency of the algorithm.