Abstract
Despite recent advancements in user-driven social media platforms, tools for studying user behavior patterns and motivations remain primitive. We highlight the voluntary nature of user contributions and that users can choose when (and when not) to contribute to the common media pool. A Game theoretic framework is proposed to study the dynamics of social media networks where contribution costs are individual but gains are common. We model users as rational selfish agents, and consider domain attributes like voluntary participation, virtual reward structure, network effect, and public-sharing to model the dynamics of this interaction. The created model describes the most appropriate contribution strategy from each user’s perspective and also highlights issues like ‘free-rider’ problem and individual rationality leading to irrational (i.e. sub-optimal) group behavior. We also consider the perspective of the system designer who is interested in finding the best incentive mechanisms to influence the selfish end-users so that the overall system utility is maximized. We propose and compare multiple mechanisms (based on optimal bonus payment, social incentive leveraging, and second price auction) to study how a system designer can exploit the selfishness of its users, to design incentive mechanisms which improve the overall task-completion probability and system performance, while possibly still benefiting the individual users.
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Notes
- 1.
The use of perceived changes in games to try and influence agent interaction is well studied under hyper-game theory [24].
- 2.
Strictly speaking, system designer needs to provide the lowest cost agent with a bonus that is just a fraction above its cost (i.e. b=c 1+ε). This will make the ‘Do’ strategy dominate for the user. However, in a cooperative setting, it is often considered better to grant a ‘fair share’ of the additional benefit the agent brings to the system by participating. Further still, the extra bonus serves as an implicit signaling mechanism to ensure overall system gains.
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Singh, V.K., Jain, R., Kankanhalli, M. (2011). Mechanism Design for Incentivizing Social Media Contributions. In: Hoi, S., Luo, J., Boll, S., Xu, D., Jin, R., King, I. (eds) Social Media Modeling and Computing. Springer, London. https://doi.org/10.1007/978-0-85729-436-4_6
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DOI: https://doi.org/10.1007/978-0-85729-436-4_6
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