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This whitepaper makes multifold contributions to the body of literature on online communities: 1) it advances our understanding of the complex relationships that exist in an online community; 2) it refines the classifications and definitions of key members in online communities based on deep-level relationships; and 3) it proposes a social computing approach to identifying key members. Compared with a traditional ethnographic approach to online community data, which requires one to read and analyze hundreds, if not thousands, of postings manually, the social computing approach presented here is much more efficient and effective by automatically identifying those members that warrant additional attention.