Abstract: A method for analyzing social network accounts includes querying a first social network for data about a first user account associated with the first social network. The received data is stored in a social graph structure and used to determine derived characteristics of the first user account. The derived characteristics are quantified and used to generate a first feature vector for the first user account. The first feature vector of the first user account is compared with a second feature vector of a second user account associated with a second social network different from the first social network. Based on the comparison of the first and second feature vectors, it is determined whether the first user account and the second user account are associated with a same entity.

Abstract: A method for analyzing data in a social network. A social graph for a user account associated with a social network is created. A social score for the user account is determined to be above a threshold, and a participation score for the user account is generated based on data associated with previous information spread events in the social network. An impact score for the user account is calculated based on the social and participation scores for the user account. A state model for a future information spread event in the social network is constructed and then run with and without the user account present. A comparison is made between the flows of information through the social network with and without the user account present in the state model, and a determination is made as to whether a difference between the flows of information satisfies a predetermined condition.