UGC collection strategy oriented user influence classification and feature analysis

With the development of Social Networking Services, users can publish and receive information expediently. With the scale of information to be processed is becoming bigger, the information acquisition rules adopted by traditional search engine met with many difficulties. To solve the problem, we must develop new UGC collection strategy. We think there are three main factors: user, UGC and the interactive relationship between user and UGC. In this paper, we propose an algorithm named UIC to calculate user influence value. Based on the results, we classify the user into three types: star user, usual user, zombie user. In order to make further analysis of features of all kinds of users, based on preliminary classification, we make sampling and content analysis of the three types of user in order to optimize the user classification, and also make better support the UGC acquisition strategy.