User-oriented social analysis across social media sites

Abstract

The vast amount of user-generated data in various and disparate social media sites contains rich and diverse information about what is happening around the world. Digging into such user-generated data distributed in different social media sites helps us better understand what people are interested in and how they feel about certain topics. In this paper, we investigate into users' behavior data in Twitter and YouTube to figure out whether people's attention on certain topics has some sort of temporal order between Twitter and YouTube on user level. We collected a real world dataset of 8,518 users with account associations between Twitter and YouTube as well as all their behavior data with timestamp since Jan. 2012. The results demonstrate that more users tend to get access to certain events earlier in Twitter than in YouTube and the ratio is somewhat topic-sensitive. © 2013 Springer-Verlag.