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

by: Ran Cheng, Julita Vassileva

User Modeling 2005 (2005), pp. 332-336.

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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.

@incollection{citeulike:1377873, 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.}, author = {Cheng, Ran and Vassileva, Julita }, citeulike-article-id = {1377873}, doi = {http://dx.doi.org/10.1007/11527886\_43}, journal = {User Modeling 2005}, keywords = {community, contribution, social-navigation}, pages = {332--336}, posted-at = {2007-10-17 01:49:12}, priority = {0}, title = {User- and Community-Adaptive Rewards Mechanism for Sustainable Online Community}, url = {http://dx.doi.org/10.1007/11527886\_43}, year = {2005} }

RIS record

TY - CHAP ID - citeulike:1377873 L3 - citeulike-article-id:1377873 N2 - 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. JF - User Modeling 2005 EP - 336 TI - User- and Community-Adaptive Rewards Mechanism for Sustainable Online Community SP - 332 KW - community KW - contribution KW - social-navigation AU - Cheng, Ran AU - Vassileva, Julita PY - 2005/// UR - http://dx.doi.org/10.1007/11527886_43 ER -

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