通过重连边提升社交网络中弱势群体的影响力公平性
Efficient Edge Rewiring Strategies for Enhancing PageRank Fairness
- 基于贪心策略与根生成树采样，设计线性时间算法优化网络结构
- 在百万节点网络上仅需几分钟即可显著改善弱势群体的PageRank公平性
- 适用于需要提升信息传播公平性的社交网络或职业平台
我们研究社交网络中的不公平现象，即在男性主导行业中女性群体因网络位置不利而难以获取重要信息（如职位招聘信息）。针对一种成熟的公平性度量——PageRank公平性（即不同群体间PageRank权重的公平分配），本文旨在通过修改网络结构来增强该公平性。具体而言，在允许重连固定数量边的前提下，最大化弱势群体的PageRank公平性。基于贪心策略，结合根生成树快速采样技术，提出一种高效线性时间算法。在多个真实世界网络数据集上进行大规模实验，结果表明该算法显著优于现有方法，可在数分钟内处理百万节点规模的网络。
原文摘要 · Abstract (English)
We study the notion of unfairness in social networks, where a group such as females in a male-dominated industry are disadvantaged in access to important information, e.g. job posts, due to their less favorable positions in the network. We investigate a well-established network-based formulation of fairness called PageRank fairness, which refers to a fair allocation of the PageRank weights among distinct groups. Our goal is to enhance the PageRank fairness by modifying the underlying network structure. More precisely, we study the problem of maximizing PageRank fairness with respect to a disadvantaged group, when we are permitted to rewire a fixed number of edges in the network. Building on a greedy approach, we leverage techniques from fast sampling of rooted spanning forests to devise an effective linear-time algorithm for this problem. To evaluate the accuracy and performance of our proposed algorithm, we conduct a large set of experiments on various real-world network data. Our experiments demonstrate that the proposed algorithm significantly outperforms the existing ones. Our algorithm is capable of generating accurate solutions for networks of million nodes in just a few minutes.
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