Finding the Spreaders in a Graph Database The use of graph databases has increased significantly in the last decades, especially for storing data in social networks (e.g. Facebook, Linkedin, etc.). An important question that has received considerable research is finding the group of spreaders or the influential nodes in a social network. These nodes are defined to be the set of nodes who collectively can reach all other nodes in the network diffusing and spreading information. These nodes can be used to drive the whole network to a certain opinion or idea, therefore finding these nodes can be of high interest to politicians and opinion makers and drivers. In this paper, we provide an algorithm that can identify the minimal set of spreaders in a database graph. The algorithm is based on first extracting the strongly connected components of the graph, and then using these to identify the set of bases of the directed graph. Each base can be used as the set of spreaders that will allow a piece of information to flow and reach all other users in the database.

Latencybounded Target Set Selection in Signed Networks It is welldocumented that social networks play a considerable role in information spreading. The dynamic processes governing the diffusion of information have been studied in many fields, including epidemiology, sociology, economics, and computer science. A widely studied problem in the area of viral marketing is the target set selection: in order to market a new product, hoping it will be adopted by a large fraction of individuals in the network, which set of individuals should we xe2x80x9ctargetxe2x80x9d (for instance, by offering them free samples of the product)? In this paper, we introduce a diffusion model in which some of the neighbors of a node have a negative influence on that node, namely, they induce the node to reject the feature that is supposed to be spread. We study the target set selection problem within this model, first proving a strong inapproximability result holding also when the diffusion process is required to reach all the nodes in a couple of rounds. Then, we consider a set of restrictions under which the problem is approximable to some extent.