Twitter offers an explicit mechanism to facilitate information diffusion and has emerged as a new medium for communication. Many approaches to find influentials have been proposed, but they do not consider the temporal order of information adoption. In this work, we propose a novel method to find influentials by considering both the link structure and the temporal order of information adoption in Twitter. Our method finds distinct influentials who are not discovered by other methods. Categories and Subject Descriptors: J.4 [Computer Applications]: Social and Behavioral Sciences General Terms: Algorithms, Measurement
Changhyun Lee, Haewoon Kwak, Hosung Park, Sue B. M