Manipulating Citation Indices in a Social Context

The h-index [6] is a popular measure of a researcher's publication activity: a researcher's h-index is the largest number χ such that she has at least χ papers that have received at least χ citations each. It has been observed that one can manipulate her h-index by strategically merging one or more articles, and the complexity of finding a successful/optimal manipulation has been investigated for a variety of models [3,11]. In this paper, we extend this line of research to two other popular citation indices, namely, the g-index [4] and the i10-index, and show that these indices are somewhat easier to manipulate than the h-index. We then consider settings where the manipulator would like to take into account the impact of her actions on other researchers (she may want to make sure that her manipulation does not harm her friends or that it hurts her competitors) or a group of researchers manipulate their indices simultaneously. We analyze the complexity of these problems, both in the worst-case and in the parameterized framework.