The Research of Forwarding Amount Prediction of Sina Microblog Based on Emotion and User Attributes

With the development of computer network technology, Sina microblogging platform have become the birthplace of the hot spots and important route of transmission. Due to the complexity of the network information, sometimes, it is necessary to control the spread of some of microblogging. The forwarding prediction system can make contribution to build a better microblogging environment. The used dataset obtained via API (Application Programming Interface, which provided by Sina Microblogging) concerning various social levels of users, such as, sites, government, schools, celebrities, etc. We have established a forwarding predictive model based on analyzing the emotional polarity of microblog, combining with user attributes. The model shows that the amount of forwarding is associated with the user´s number of fans and the emotional polarity of microblog. The test result shows that the model has a good accuracy.