在签署的多数投票意见模型中,引导两极分化走向共识.
Masaki Chujyo1, Shu Liu2, Fujio Toriumi2
1School of Engineering, University of Tokyo, Tokyo, 113-8656, Japan. mchujyo@g.ecc.u-tokyo.ac.jp.
Scientific reports
|November 13, 2025
概括
在签名的社交网络中,一种新的偏见可以消除两极分化,促进共识. 这种结构意识的干预甚至在具有许多对立关系的大型网络中也是有效的.
科学领域:
- 社交网络分析分析
- 计算社会科学 计算社会科学
- 意见的动态意见的动态.
背景情况:
- 签名社会网络,代表积极和消极的关系,往往导致持久的意见两极分化.
- 了解和缓解这种两极分化对于社会凝聚力至关重要.
研究的目的:
- 开发和评估一种方法来消除签名社会网络中的两极分化.
- 调查动态,符号匹配边缘偏差在促进共识方面的有效性.
主要方法:
- 修改快速梯度标志方法,包括一个统一的,标志匹配的边缘偏差.
- 在合成图表和大型现实数据集上进行的实验.
主要成果:
- 建议偏见的适度水平有效地消除了两极分化,并促进了广泛的共识.
- 相比之下,强度匹配的随机扰动可以保持意见分歧.
- 需要的偏差随着对抗关系的密度增加而增加,但对网络大小相对不敏感.
结论:
- 轻量级,结构意识的干预可以在大型签名网络中恢复共识.
- 这种方法提供了一个可行的策略来缓解在线社会分裂和两极分化.
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