自学和社会学习对语言动态的集体影响:社交网络中的命名游戏方法
Tao Wen1,2, Yu-Wang Chen1,2, Renaud Lambiotte2,3
1Decision and Cognitive Sciences Research Centre,The University of Manchester, Manchester M15 6PB, UK.
Journal of the Royal Society, Interface
|December 4, 2024
概括
这项研究使用命名游戏来建模学习和记忆等社会行为如何影响语言规则. 网络结构和社会学习显著影响语言规范化和意见动态.
科学领域:
- 复杂性科学 复杂性科学
- 决策科学 决策科学 决策科学
- 计算语言学 计算语言学
背景情况:
- 人类的沟通依赖于语言规则,但像不规则的过去时代动词这样的例外会带来挑战.
- 了解语言动态需要研究社会行为如何影响规则的采用和规范化.
研究的目的:
- 用命名游戏方法研究社会行为对语言动态的集体影响.
- 在社会学习模型中引入评估个人影响力和亲和力的特征.
- 分析网络结构和社会行为对语言规范化和意见转变的影响.
主要方法:
- 开发了一个命名游戏模型,结合了社会学习,有偏好的自我学习和忘记.
- 介绍了基于贝叶斯推理的社会学习的个人影响力和亲和力指标.
- 检查了各种结构的合成和现实世界的网络上的语言动态.
主要成果:
- 网络异质性和社区结构显著影响语言动态.
- 自我学习大大提高了语言的规范化,而遗忘却有很小的影响.
- 社会行为和网络结构影响了观点从共识到两极分化的转变.
结论:
- 个体学习者采用网络结构和社会行为影响的语言规则.
- 复杂性和决策科学观点为语言动态提供了洞察力.
- 社会影响和学习机制对于理解语言演变至关重要.
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