Identifying Super-Mediators of Information Diffusion in Social Networks Kazumi Saito 1 , Masahiro Kimura 2 , Kouzou Ohara 3 , and Hiroshi Motoda 4 1 School of Administration and Informatics, University of Shizuoka k-saito@u-shizuoka-ken.ac.jp 2 Department of Electronics and Informatics, Ryukoku University kimura@rins.ryukoku.ac.jp 3 Department of Integrated Information Technology, Aoyama Gakuin University ohara@it.aoyama.ac.jp 4 Institute of Scientific and Industrial Research, Osaka University motoda@ar.sanken.osaka-u.ac.jp Abstract. We propose a method to discover a different kind of influential nodes in a social network, which we call “super-mediators”, i.e., those nodes which play an important role in receiving the information and passing it to other nodes. We mathematically formulate this as a difference maximization problem in the average influence degree with respect to a node removal, i.e., a node that con- tributes to making the difference large is influential. We further characterize the property of these super-mediators as having both large influence degree, i.e., ca- pable of widely spreading information to other recipient nodes, and large reverse- influence degree, i.e., capable of widely receiving information from other infor- mation source nodes. We conducted extensive experiments using three real world social networks and confirmed that this property holds. We further investigated how well the conventional centrality measures capture super-mediators. In short the in-degree centrality is a good measure when the diffusion probability is small and the betweenness centrality is a good measure when the diffusion probability is large, but the super-mediators do depend on the value of the diffusion proba- bility and no single centrality measure works equally well for a wide range of the diffusion probability. Keywords: Information diffusion, super-mediator, influence degree, reverse- influence degree 1 Introduction The emergence of Social Media such as Facebook, Digg and Twitter has provided us with the opportunity to create large social networks, which play a fundamental role in the spread of information, ideas, and influence. Such effects have been observed in real life, when an idea or an action gains sudden widespread popularity through “word-of- mouth” or “viral marketing” effects. This phenomenon has attracted the interest of many researchers from diverse fields [12], such as sociology, psychology, economy, computer science, etc.