Event Multiple Influence Calculation and Relationship of Multiple Influence Discovery

Abstract

Abstract-Due to the development of web technology, the research on Internet big data become more and more popular. However, information presents polymorphism and complexity under the status of the rapid development of Internet big data. Most of the traditional methods of event influence calculation use observable data to evaluate and ignore the decay influence of event. In fact, event influence growths from the moment of event happening to the end, meanwhile, it accompanis with a certain decay. What's more, event influence presents observable influence and decay influence on different network media. This paper proposes a new method to calculate event influence on different network media and find the relationships between observable influence and decay influence on different stages of event. Experiments show that better influence calculation will be achieved by decay algorithm based on Ebbinghaus forgetting curve and information fusion by considering interaction between observable influence and decay influence.