Influence Maximization Of Enterprise Public Opinion Based On Weibo Platform

As an important part of Web2.0,Social networks can not be ignored in social information spread.Nowdays,weibo,one of the social networks,has a strong vitality and continues good development.Enterprises search for brand promotion and product marketing through the weibo platform.Bsed on this phenomenon,more and more enterprises choose weibo platform to spread the opinion so that they can maximize the influence scope.However,enterprise can hardly spread information to every user in weibo because of real factors,so enterprises will choose an initial subset of nodes in weibo that could maximize the spread of influence.According to this background,this paper defines a new social network influence maximization problem: enterprise opinion influence maximization problem with limited cost.What's more,this paper construct one model to express this problem.To solve this problem,first,topic-based element is added into the above problem so that the new problem can accord with the real environment.Then,this paper takes influence maximization problem with limited cost into research.Last,this paper utilizes genetic algorithm to solve the above problem through experiments.Genetic algorithm can not only solve the influence problem effectively,but also enterprise opinion reason.By investigating topic-based influence maximization problem with limited cost,we can get some useful meanings on advertisement marketing and brand trademark.With limited cost and given enterprise opinion,we can choose a proper subset of people to express message,and we can make different enterprise opinions influence as much as scope in weibo platform.