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One of the issues with using social networks for analysis is the problem of having missing nodes in the network. Having missing nodes can significantly impact the results of the analysis, and should be avoided as much as possible. For social network analysis to be more effective for criminal networks, where there are likely missing nodes, the number of missing nodes needs to be reduced. This research provides a method to help identifying hidden nodes in a network using previously collected social network data. In general the main idea is to take a social network and match the nodes of that network to the nodes of a previous social network, such that most of the overall structure of the social network is maintained. This mapping is completed by using various measures of the social network as distance measures. The outputted information will help investigators identify the importance of the missing nodes, and decide whether the missing nodes are significant enough to spend the time to uncover or not.