在社交网络上,通过随机的推动来消除观点的两极分化
Ritam Pal1, Aanjaneya Kumar1, M S Santhanam1
1Department of Physics, Indian Institute of Science Education and Research, Dr. Homi Bhabha Road, Pune 411008, India.
Physical review. E
|October 18, 2023
概括
轻微推动在线社交网络代理人形成随机连接可以减少意见两极分化和回声室. 最佳的推动避免了两极分化和激进化,促进了更健康的在线话语.
科学领域:
- 计算社会科学 计算社会科学
- 统计物理 统计物理
- 网络科学 网络科学
背景情况:
- 在线社交网络表现出意见两极分化和回声室.
- 传统的论动态模型无法解释这些现象.
- 基于同性恋的模型捕捉了两极化,但没有缓解策略.
研究的目的:
- 引入一个框架来缓解在线网络中的两极化和回声室.
- 调查引入代理人之间的随机连接的影响.
- 确定最佳的干预策略,以平衡论动态.
主要方法:
- 开发了一个非侵入性的框架,以"推动"代理人实现随机连接.
- 模拟的意见动态,包括同性恋和随机连接.
- 分析了nudge概率对意见分布和网络结构的影响.
主要成果:
- 轻微的推动显著地使意见脱极化,并减少了回声室.
- 过度推动可以导致激进化,这是一个不良结果.
- 确定了一个最佳的推动概率,以防止两极化和激进化.
结论:
- 引入随机连接是打击在线意见两极分化的一个有效策略.
- 仔细校准干预措施至关重要,以避免像激进化这样的意外后果.
- 该研究提供了一种培养更多多样化和较少两极分化的在线社区的方法.
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