Abstract:

In campus networks,there are a large number of information systems that record the users’ daily behavior. By analyzing the daily trajectory information of a large number of users, we can find the behavioral correlation among users, and measure the strength of social relationship among users. Based on the data characteristics of the campus network systemin a Shanghai college, we propose an improved method based on user time series model, which utilizes the shortest time distance to measure the social relationship among users. This method firstly uses the users’ behavioral data to generate the time series for users. Based on the time series, it measures the behavioral correlation between two users to quantify the strength of users’ social relationship in the real world. Location popularity is used to correct the analysis of the social relationship strength. In the experiment, we apply the method to analyze the data of the campus network system in one Shanghai college, measue the strength of correlation among users, and verify the effectiveness of the method.

Key words: trajectory data;time series model;measurement of users&rsquo, correlation;cluster analysis