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Title: Intelligent support for knowledge sharing in virtual communities
Author: Kleanthous Loizou, Styliani
ISNI:       0000 0004 2698 0211
Awarding Body: University of Leeds
Current Institution: University of Leeds
Date of Award: 2010
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Virtual communities where people with common interests and goals communicate, share resources, and construct knowledge, are currently one of the fastest growing web environments. A common misconception is to believe that a virtual community will be effective when people and technology are present. Appropriate support for the effective functioning of online communities is paramount. In this line, personalisation and adaptation can play a crucial role, as illustrated by recent user modelling approaches that support social web-groups. However, personalisation research has mainly focused on adapting to the needs of individual members, as opposed to supporting communities to function as a whole. In this research, we argue that effective support tailored to virtual communities requires considering the wholeness of the community and facilitating the processes that influence the success of knowledge sharing and collaboration. We are focusing on closely knit communities that operate in the boundaries of organisations or in the educational sector. Following research in organisational psychology, we have identified several processes important for effective team functioning which can be applied to virtual communities and can be examined or facilitated by analysing community log data. Based on the above processes we defined a computational framework that consists of two major parts. The first deals with the extraction of a community model that represents the whole community and the second deals with the application of the model in order to identify what adaptive support is needed and when. The validation of this framework has been done using real virtual community data and the advantages of the adaptive support have been examined based on the changes happened after the interventions in the community combined with user feedback. With this thesis we contribute to the user modelling and adaptive systems research communities with: (a) a novel framework for holistic adaptive support in virtual communities, (b) a mechanism for extracting and maintaining a semantic community model based on the processes identified, and (c) deployment of the community model to identify problems and provide holistic support to a virtual community. We also contribute to the CSCW community with a novel approach in providing semantically enriched community awareness and to the area of social networks with a semantically enriched approach for modeling change patterns in a closely-knit VC.
Supervisor: Dimitrova, V. G. Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available