Research On Minimal Cost And Time-critical Information Dissemination In On-line Social Networks

With the rapid development of information technology, more and more people participate in social networks, people are willing to share information in the network, expand their contacts, and companies can also directly impact on customers through social networks platforms. Online social networks have become an indispensable part of people's life. Various fields pay attention to the social networks analysis related work. Information diffusion research is one of the important branches of social network analysis. Information diffusion research has its own characteristics and difficulties. First, the online social network is too large to design an efficient method. Second, the diversity of the model should be designed according to the actual situation. In order to solve these problems, the study of information diffusion in online social networks is full of challenges and opportunities. Deal with the information diffusion in on-line social networks problem, the following work has been done in two aspects, the cost factor and the time factor.In consideration of the research on the different users with different costs is less in the present research on the influence maximization problem, this paper presents a heuristic algorithm called MODC to solve the cost sensitive influence maximization problem. The MODC algorithm not only takes the network structure into account but also consideration of the cost factor, it will add the user with higher proportion of the degree and price to the seed. By comparing the MODC, MOW and MOD with different data sets and different cost distributions, the MODC algorithm is better than the MOD and MOW algorithm.In the online social networks, the time delay of the information is always caused by the on-line rules. Based on the weight cascade model, the time-critical propagation model is designed by add the online mode. Then, in order to solve the time-critical information diffusion problem, the GAOP algorithm is designed. It simulates information diffusion process in time-critical propagation model by time slices in turn, and it selects the user who has maximum marginal gain influence. The effect of GAOP and other algorithms are compared under different time factors. According to the results of the experiment, in the case of different information release time and deadline, the GAOP algorithm is better than other algorithms. At the same time, this paper shows the importance of the time factor to the information diffusion, and analyzes how the time factor affects the information diffusion.