1. A method comprising: processing social network data using one or more processors to establish a tensor model of the social network data, the tensor model having at least an order of four; decomposing the tensor model using the one or more processors into a plurality of principal factors, wherein each principle factor of the plurality of principal factors refers to a corresponding set of vectors whose corresponding outer products are corresponding rank-one tensors which results from tensor decomposition, and wherein the each principal factor comprises a corresponding projection of the tensor model onto tensor space with only one corresponding direction that combines information from all dimensions of the tensor model; synthesizing, using the one or more processors, and from a subset of the plurality of principal factors, a summary tensor representing a plurality of relationships among a plurality of entities in the tensor model, such that a synthesis of relationships is formed and stored in one or more non-transitory computer readable storage media; identifying, using the one or more processors and further using one of the summary tensor and a single principal factor in the subset, at least one parameter selected from the group consisting of: a correlation among the plurality of entities, a similarity between two of the plurality of entities, and a time-based trend of changes in the synthesis of relationships; and communicating the at least one parameter.