Gonorrhea incidence forecasting research based on Baidu search data

The popularization of the Internet provide people with more quick and direct access to information channel, the network search data record the netizens´ tens of thousands of search concerns and needs to provide the necessary data base for the research of social and economic behavior. Search behaviors´ anonymity just can meet the venereal-disease suspected patients´ privacy need. This paper will use search data in the prediction of the incidence of gonorrhea, begin from theory analysis to reveal the relationship between the Baidu search keyword search volume and gonorrhea incidence, and then apply quantitative empirical analysis methods, after that dirive four key factors from 206 search data derived using statistics method and the factor analysis method, finally establish the model between gonorrhea incidence and Baidu search data, validate significant correlation between them. The conclusion can provide a certain gonorrhea incidence prediction reference for Chinese Center For Disease Control And Prevention, and the method discussed in this paper also can be used for other network economic behavior prediction and can also provide reference.