Data Collection and Modeling of Personal Social Behaviors

Abstract

Social media has developed rapidly, which had already affected modern people's life style. Meanwhile, social media has produced huge amounts of data. In research, we find that there is no explicit definition of user's behavior pattern in social network. Therefore, we focused on the research of that and found people who have two types of behaviors which are inseparably intertwined. The two types that mentioned are functional behaviors and social behaviors. We have defined user's behavior, and regarded user's behavior as a vertical timeline which the object of study is individual. With adding some horizontal lines which stand for social behaviors between vertical timelines, the model linked different people. Experiment's research takes Sina Weibo as an object. For obtaining the social behavior pattern, we use the generalized sequential pattern algorithm (GSP) for data mining. And the pattern is represented by the form of [User Behavior User a#x2192; User Behavior User]*n. According to the result and algorithm accuracy confirmation, the frequent behavioral patterns of a certain person can be obtained. After that we can also predict user's behaviors in the future.