Social computing and user-generated content: a game-theoretic approach
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[1] R. Preston McAfee,et al. Crowdsourcing with endogenous entry , 2012, WWW.
[2] Patrick Hummel,et al. A game-theoretic analysis of rank-order mechanisms for user-generated content , 2011, EC '11.
[3] Jiang Yang,et al. Seeking and Offering Expertise Across Categories: A Sustainable Mechanism Works for Baidu Knows , 2009, ICWSM.
[4] Fang Wu,et al. Crowdsourcing, attention and productivity , 2008, J. Inf. Sci..
[5] Mark S. Ackerman,et al. Questions in, knowledge in?: a study of naver's question answering community , 2009, CHI.
[6] Robert E. Kraut,et al. Experiment 1 : Motivating Conversational Contributions Through Group Homogeneity and Individual Uniqueness , 2010 .
[7] Patrick Hummel,et al. Implementing optimal outcomes in social computing: a game-theoretic approach , 2012, WWW.
[8] Patrick Hummel,et al. Learning and incentives in user-generated content: multi-armed bandits with endogenous arms , 2013, ITCS '13.
[9] R. Preston McAfee,et al. Incentivizing high-quality user-generated content , 2011, WWW.
[10] Mark S. Ackerman,et al. Virtual gifts and guanxi: supporting social exchange in a chinese online community , 2011, CSCW.