Detecting changes over time in a knowledge sharing community

There is an establishing trend towards the socialization of the web. Virtual communities are becoming very popular web spaces for collaboration and knowledge sharing. However, studies have shown that virtual communities may often be ineffective and may not sustain. We propose a novel approach for community-tailored support which is aimed at facilitating processes important for the community's effectiveness and sustainability. The paper presents algorithms for detecting evolution patterns of community knowledge sharing behavior. The algorithms are applied to a model of an existing closely-knit community, and used to identify when and what intelligent interventions may be needed to support the functioning of the community as an entity.