Nodal Degree Correlations Around Twitter’s Influencers Revealed by Two-Hop Followers

Author:

Takano Chisa,Aida Masaki, ,

Abstract

In recent years, with the spread of social networking services (SNSs), communication has been facilitated among people regardless of age, occupation, and geographical locations. The SNSs are used not only for directly developing friendships, but also as a tool for spreading friendships, allowing users to exchange information in real-time with people having common interests. Twitter, in particular, is a service with a large number of users and a considerable influence on information diffusion. In this study, the characteristics of the follower networks centered on various Twitter influencers are analyzed, and the common characteristics that do not depend on individual influencers are clarified for the world-famous influencers (US and international). Furthermore, after theoretically analyzing the relationship between the characteristics of the nodal degree distribution and the degree correlation, the degree dependence of the correlation coefficient expressing the degree correlation is clarified using numerical experiments.

Funder

Japan Society for the Promotion of Science

Publisher

Fuji Technology Press Ltd.

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Human-Computer Interaction

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