A system and method are provided for determining influence spread in social networks. The method includes generating a plurality of samples using a computing device, each sample corresponding to a collection of all edge weights for a social network graph topology; and allocating, by the computing device, the plurality of samples into at least one batch, a size of which is being determined according to a number of threads and global memory space available in a multi-processor platform. For each batch, the method includes parallel processing the samples in that batch using the multi-processor platform to generate results corresponding to a spread of each graph node per sample in that batch; storing results of that batch in the global memory accessible to the multi-processor platform; and sending the results to the computing device. The method also includes computing, using the computing device, an average spread of each node across all samples in all batches; and determining, from the average spreads, one or more nodes having a largest spread.
Data Infrastructure and Method for Estimating Influence Spread in Social Networks