Information modeling is required for creating a successful information system while modeling of communities is pivotal for maintaining community information systems(CIS). Online social media, a special case of CIS, have been intensively used but not usually adopted for learning community needs. Thus community stakeholders meet problems by supporting learning communities in social media. Under the prism of Community of Practice theory, such communities have three dimensions that are responsible for community sustainability: mutual engagement, joint enterprises and shared repertoire. Existing modeling solutions use either perspectives of learning theories, or analysis of learner or community data captured in social media but rarely combine both approaches. Therefore, current solutions produce community models that supply only a part of community stakeholders with information that can hardly describe community success and failure. We also claim that community models must be created based on community data analysis integrated with our learning community dimensions. Moreover, the models need to be adapted according to environmental changes.This work provides a solution to continuous modeling of informal learning communities in social media. In particular, it makes the following contributions: 1. A metamodel of learning communities and its specific cases in social media. 2. A process of continuous community model creation that consists of four phases that model, refine, monitor and analyze learning communities. The phases and their realizations can be used to model any learning community with the purpose to support community evolution and to improve social media facilities to satisfy community needs. 3. Methods for community data analysis and storage have been exploited for retrieving learning community states to manage competences in a collaborative space and specifying culturally sensitive requirements of communities towards social media. 4. Our formal representation of a learning community has been used to model early requirements of learning communities and their evolution and to validate the effectiveness of possible community changes through multi-agent simulation.
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