Predicting viral Marketing Propagating Efficiency within given Deadline

As a new developed marketing strategy in recent years, viral marketing attracts great attention from scholars and enterprises. Many enterprises try to adopt it for marking new product in order to greatly improve large sales and to quickly recoup the cost. But how marketing efficiency is actually? How fast marketing propagating speed is on earth? Especially for a given deadline, can the enterprise predict the sales when viral marketing is used? In this paper, a predicting method based on deadline graph is proposed to evaluate the viral marketing efficiency within given deadline. Specifically, two methods are first proposed to generate deadline graph, respectively Shortest-Distance methods and Time-Iteration method, based on which, a Reverse Tree method is exploited to predict the activated (buying) probability of the users. A lot of experiments are made to test our proposed method by using three datasets, respectively Twitter, Friendster and Random. The experiment results clearly show that deadline graph is a very key and necessary technique for evaluating viral marketing propagating efficiency within given deadline since overwhelming advantages over traditional method are gained by the method based on deadline graph in our experiment.