A Centrality for Social Media Users Focusing on Information-Gathering Ability

In this paper, we propose a centrality metric for social media users that focuses on their information-gathering ability. Existing methods of rating users in social graphs focus on various aspects of users, such as popularity, influential power, and informational quality, but these aspects are related to information-transmitting ability of users. On social media, information-gathering ability is also an important ability, which varies widely from user to user. There have been two well-known metrics related to it: the hub score in the HITS algorithm and Katz centrality. These two methods are, however, not designed for today's social media, and do not take important aspects of social media into consideration. HITS does not consider multi-hop information propagation, and Katz centrality assumes that all nodes in the graph are equally important as information sources and also as information propagation mediators. In the proposed method, we extend Katz centrality by introducing two properties of users: importance as information source and information forwarding probability. The result of our experiment on two Twitter follow graphs shows that our metric produces a ranking different from the existing metrics, and also suggests that it captures some useful aspect of users that are not captured by existing metrics.