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User- and Community-Adaptive Rewards Mechanism for Sustainable Online Community

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User Modeling 2005 (UM 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3538))

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Abstract

Abundance of user contributions does not necessarily indicate sustainability of an online community. On the contrary, excessive contributions in the systems may result in “information overload” and user withdrawal. We propose an adaptive rewards mechanism aiming to restrict the quantity of the contributions, elicit contributions with higher quality and simultaneously inhibit inferior ones. The mechanism adapts to the users preferences with respect to types of contributions and to the current needs of the community depending on the time and the number of existing contributions.

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References

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Author information

Authors and Affiliations

  1. Computer Science Department, University of Saskatchewan, Saskatoon, SK, S7N 5A9, Canada

    Ran Cheng & Julita Vassileva

Authors
  1. Ran Cheng
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  2. Julita Vassileva
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Editor information

Editors and Affiliations

  1. Dipartimento di Informatica, Università di Torino, Corso Svizzera 185, 10149, Torino, Italy

    Liliana Ardissono

  2. The SCRE Centre, University of Glasgow, 11 Eldon Street, P.O. Box, G3 6NH, Glasgow, United Kingdom

    Paul Brna

  3. Intelligent Computer Tutoring Group, Department of Computer Science and Software Engineering, University of Canterbury, Private Bag 4800, P.O. Box, Christchurch, New Zealand

    Antonija Mitrovic

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© 2005 Springer-Verlag Berlin Heidelberg

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Cheng, R., Vassileva, J. (2005). User- and Community-Adaptive Rewards Mechanism for Sustainable Online Community. In: Ardissono, L., Brna, P., Mitrovic, A. (eds) User Modeling 2005. UM 2005. Lecture Notes in Computer Science(), vol 3538. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11527886_43

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  • DOI: https://doi.org/10.1007/11527886_43

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-27885-6

  • Online ISBN: 978-3-540-31878-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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