Collective Intelligence: Mankind's Emerging World in Cyberspace
Collective Intelligence: Mankind's Emerging World in Cyberspace
Reputation Mechanism Design in Online Trading Environments with Pure Moral Hazard
Information Systems Research
Computer
Identifying user behavior in online social networks
Proceedings of the 1st Workshop on Social Network Systems
Social comparisons to motivate contributions to an online community
PERSUASIVE'07 Proceedings of the 2nd international conference on Persuasive technology
Image-based dietary information mining for community creation in a social network
Proceedings of second ACM SIGMM workshop on Social media
Understanding contextual factors in location-aware multimedia messaging
International Conference on Multimodal Interfaces and the Workshop on Machine Learning for Multimodal Interaction
Causal discovery in social media using quasi-experimental designs
Proceedings of the First Workshop on Social Media Analytics
Why do we converse on social media?: an analysis of intrinsic and extrinsic network factors
WSM '11 Proceedings of the 3rd ACM SIGMM international workshop on Social media
Tagging tagged images: on the impact of existing annotations on image tagging
Proceedings of the ACM multimedia 2012 workshop on Crowdsourcing for multimedia
Linked data in crowdsourcing purposive social network
Proceedings of the 22nd international conference on World Wide Web companion
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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. We use a Game theoretic framework to study the dynamics of a social media network wherein 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 and public-sharing to model the dynamics of this interaction. The created model describes the most appropriate contribution strategy from each user's perspective. Next, we consider the problem of mechanism design from a system designer's perspective who is interested in finding the optimal incentive levels to influence the selfish end-users so that the overall system utility is maximized. We demonstrate how a system administrator can exploit the selfishness of its users, to design incentive mechanisms which help in improving the overall task completion probability and system performance, while possibly still benefiting the individual users.