We present a generalized method for calculating the k-shell structure of weighted networks. The method takes into ac 80b count both the weight and the degree of a network, in such a way that in the absence of weights we resume the shell structure obtained by the classic k-shell decomposition. In the presence of weights we show that the method is able to partition the network in a more refined way, without the need of any arbitrary threshold on the weight values. Furthermore, by simulating spreading processes using the Susceptible-Infectious-Recovered model in four different real weighted networks, we show that the weighted k-shell decomposition method ranks the nodes more accurately, by placing nodes with higher spreading potential into shells closer to the core. In addition we demonstrate our new method on a real economic network and show that the core calculated using the weighted k-shell method is more meaningful from an economics perspective when compared to the unweighted method.