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The technique of Agent-Based Modeling (ABM) is increasingly well known in the social sciences. However its associated methodology, partly through neglect within the ABM community itself, is much less well known. It is this methodology that justifies any claim that ABM may try to make that it is a distinctive way of doing social science. It also gives ABM a distinctive relationship with commonly available forms of social science data (quantitative and qualitative). This talk uses two simple examples of ABM (one network based and the other not) to justify the claim that ABM is a distinctive approach to social science (and data) when it follows a particular methodology. It also touches briefly on the implications of non-linearity in social systems for the potential inadequacy of qualitative and quantitative approaches operating in isolation. The main part of the talk will build on this insight to investigate the key role that ABM could play in understanding social networks with particular reference to existing Social Network Analysis (SNA) approaches and the prevailing “separatist” use of qualitative and quantitative data.