Towards Consensus: Reducing Polarization by Perturbing Social Networks
Towards Consensus: Reducing Polarization by Perturbing Social Networks
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DOI：
10.1109/tnse.2023.3262970
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发表时间：
2022-06
影响因子：
6.6
通讯作者：
Miklós Z. Rácz;Daniel E. Rigobon
中科院分区：
文献类型：
--
作者：
Miklós Z. Rácz;Daniel E. Rigobon
本文研究了集中式规划师如何修改社会或信息网络的结构以减少两极分化。不断）。 Laplacian的频谱差距证明了策略的有效性，该策略在频谱差距的特征向量引起的相对侧面的顶点是在六个现实世界中评估这些策略的。我们发现，通过添加少量边缘可以显着降低极化。
This article studies how a centralized planner can modify the structure of a social or information network to reduce polarization. First, polarization is found to be highly dependent on degree and structural properties of the network – including the well-known isoperimetric number (i.e., Cheeger constant). We then formulate the planner's problem under full information, and motivate disagreement-seeking and coordinate descent heuristics. A novel setting for the planner in which the population's innate opinions are adversarially chosen is introduced, and shown to be equivalent to maximization of the Laplacian’s spectral gap. We prove bounds for the effectiveness of a strategy that adds edges between vertices on opposite sides of the cut induced by the spectral gap's eigenvector. Finally, these strategies are evaluated on six real-world and synthetic networks. In several networks, we find that polarization can be significantly reduced through the addition of a small number of edges.