This paper describes the use of content analysis and Bayesian Belief Network (BBN) techniques aimed at modelling social capital (SC) in virtual learning communities (VLCs). An initial BBN model of online SC based on previous work is presented. Transcripts drawn from two VLCs were analysed and inferences were drawn to build scenarios to train and update the model. The paper presents three main contributions. First, it extends the understanding of SC to VLCs. Second; it offers a methodology for studying SC in VLCs. Third the paper presents a computational model of SC that can be used in the future to understand various social issues critical to effective interactions in VLCs.
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