# Incentivize Diffusion with Fair Rewards

arXiv: https://arxiv.org/abs/1910.09268 · HTML: https://mlsanity.com/paper/1910.09268/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Oct 2019.

## Built on by (most cited first, 2 of 2)

- [Emerging Methods of Auction Design in Social Networks](https://mlsanity.com/paper/2108.00381/) (2021)
- [GAC: A Deep Reinforcement Learning Model Toward User Incentivization in Unknown Social Networks](https://mlsanity.com/paper/2203.09578/) (2022)

## Abstract (arXiv)

This paper studies a sale promotion mechanism design problem on a social network, where a node (a seller) sells one item to the other nodes on the network to maximize her revenue. However, the seller does not know other nodes except for her neighbours and her neighbours have no incentive to promote the sale. Hence, the goal is to design an auction mechanism such that the seller's neighbours are incentivized to invite their neighbours to join the auction, while the seller's revenue is guaranteed to increase. This is not achievable with traditional mechanisms. One solution has been proposed recently by carefully designing a reward scheme for the nodes who have invited others. However, the solution only gives rewards to some cut-points of the network, but cut-points rarely exist in a well-connected network, which actually disincentivizes nodes' participation. Therefore, we propose another novel mechanism to reward more related participants with fairer rewards, and the seller's revenue is not reduced.