Ji, Q., Shen, H., Mao, Y. & Zhu, Y. (2014). Stimulating high quality social media through knowledge barter-auctioning. SocialCom '14: Proceedings of the 2014 International Conference on Social Computing 4-11. United States of America: Association for Computing Machinery (ACM). Retrieved from https://doi.org/10.1145/2639968.2640068
Incentives play a pivotal role in stimulating user-generated content (UGC), which is critical to the viability and success of today's social computing services. Non-financial social incentives are generally effective in boosting the quantity, but have limited effect on the quality. Conversely, financial incentives generally motivate better quality, but often complicate the efforts to attract quantity. In this paper, we propose knowledge barter-auctioning, a non-financial remunerative mechanism that is particularly effective in stimulating the quality of UGC yet without detriment to its quantity. This mechanism provides an optimal way for the knowledge vendor to choose the best barter partner in order to maximise their expected revenue, which is an extrinsic motivation for the triumph of quality as UGC of higher quality will enable the vendor to attract more bidders and consequently make a higher revenue through the barter auction. We have conducted a series of experiments using a real-world dataset to analyse the ramifications of UGC quality in knowledge bartering processes.
Peter Faber Business School
Open Access Conference Paper