Abstract
This paper describes a method for scoring the degree of contribution of each information object and each participant in a cyberspace community, e.g., knowledge management and product reviews, or other information sharing communities. Two types of actions, i.e., information provisioning and information evaluation, are common in such communities and are valuable in scoring each contribution. The EigenRumor algorithm, proposed here, calculates the contribution scores based on a link analysis approach by considering these actions as links from participants to information objects. The algorithm has similarities to Kleinberg’s HITS algorithm in that both algorithms are based on the mutually reinforcing relationship of hubs and authorities but the EigenRumor model is not structured from page-to-page links but from participant-to-object links and is extended by the introduction of several new factors. The scores calculated by this algorithm can be used to identify “good” information and participants who contribute much to a community, which allows for the provisioning of incentives to such participants to promote their continuous contribution to the community.
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Fujimura, K., Tanimoto, N. (2005). The EigenRumor Algorithm for Calculating Contributions in Cyberspace Communities. In: Falcone, R., Barber, S., Sabater-Mir, J., Singh, M.P. (eds) Trusting Agents for Trusting Electronic Societies. TRUST TRUST 2004 2003. Lecture Notes in Computer Science(), vol 3577. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11532095_4
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DOI: https://doi.org/10.1007/11532095_4
Publisher Name: Springer, Berlin, Heidelberg
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