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In this paper, we present a methodology, called Homology Graph Mining, for computer-aided extraction of Social Network rules from consolidated homology graphs of statements. First, we will generate homology sources of a set of heterogeneous social networks resources in terms of relevant pathway. Second, combine a homology graph by means of homology integration of the social network resources. Third, Search and Analyze patterns from the graph. Fourth, generate and evaluate a set of candidate social network rules, which are maintained and indexed for interactive discovery of actionable rules. As part of implementation efforts of the methodology, framework architecture of specialized interrelated knowledge discovery services is proposed, and an application in biomedicine is initiated.