Abstract
Since the emergence of Web 2.0, the idea of online knowledge sharing has been gaining attention of researchers and online communities. We can observe the popularity of such services on Wikipedia and numerous Q&A systems, in which ordinary users can explicitly ask questions and provide answers thus raise their expertise level by learning from others. Users dynamically switch between roles of content producer and content consumer. This paper applies game-theoretic approach to study how different community member profiles and reputation can affect the learning process and, in consequence, credibility of the provided information.
Research supported by the grant ”Reconcile: Robust Online Credibility Evaluation of Web Content” from Switzerland through the Swiss Contribution to the enlarged European Union.
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Kowalik, G., Adamska, P., Nielek, R., Wierzbicki, A. (2014). Simulations of Credibility Evaluation and Learning in a Web 2.0 Community. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2014. Lecture Notes in Computer Science(), vol 8468. Springer, Cham. https://doi.org/10.1007/978-3-319-07176-3_33
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DOI: https://doi.org/10.1007/978-3-319-07176-3_33
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