Compensatory seeding in networks with varying avaliability of nodes
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
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A problem in the social-network-based intaraction distribution is that people are less motivated to forward information when psychological forwarding cost is large. The simplest solution for this is to compensate for the cost by giving people incentive reward when they forward information. However, it is unclear that, even if we successfully propagate information over the whole social network by the incentive reward, this propagation is meaningful for the sender (original information source). Therefore, in this paper, we propose a novel incentive rewarding method where incentive reward is assigned to a forwarder only when the receiver reacts to the forwarded information. In our method, forwarders are motivated to attach their own recommendation comment when they forward information. As a result, our method can promote receivers to react the information without increasing the total amount of incentive reward, compared with the method that gives incentive reward independently of the receiver's reaction.