[论文解读] A model of grassroots changes in linguistic systems

Janet B. Pierrehumbert, Forrest Stonedahl+1 more|arXiv (Cornell University)|Aug 8, 2014

Opinion Dynamics and Social Influence参考文献 44被引用 9

一句话总结

本文提出了一种基层语言演变的计算模型，表明普通个体——而非高地位或人脉广泛的人——可以通过规则化与概率性模仿的平衡，推动任意语言创新的广泛传播。通过在社交网络上进行蒙特卡洛模拟，研究识别出一种特定情境：适度的规则化使普通个体能够发起通过信息级联传播的变革，从而挑战了‘唯有影响力人物推动语言演变’的传统假设。

ABSTRACT

Linguistic norms emerge in human communities because people imitate each other. A shared linguistic system provides people with the benefits of shared knowledge and coordinated planning. Once norms are in place, why would they ever change? This question, echoing broad questions in the theory of social dynamics, has particular force in relation to language. By definition, an innovator is in the minority when the innovation first occurs. In some areas of social dynamics, important minorities can strongly influence the majority through their power, fame, or use of broadcast media. But most linguistic changes are grassroots developments that originate with ordinary people. Here, we develop a novel model of communicative behavior in communities, and identify a mechanism for arbitrary innovations by ordinary people to have a good chance of being widely adopted. To imitate each other, people must form a mental representation of what other people do. Each time they speak, they must also decide which form to produce themselves. We introduce a new decision function that enables us to smoothly explore the space between two types of behavior: probability matching (matching the probabilities of incoming experience) and regularization (producing some forms disproportionately often). Using Monte Carlo methods, we explore the interactions amongst the degree of regularization, the distribution of biases in a network, and the network position of the innovator. We identify two regimes for the widespread adoption of arbritrary innovations, viewed as informational cascades in the network. With moderate regularization of experienced input, average people (not well-connected people) are the most likely source of successful innovations. Our results shed light on a major outstanding puzzle in the theory of language change. The framework also holds promise for understanding the dynamics of other social norms.

研究动机与目标

• 解释缺乏功能优势的任意语言创新如何在人类群体中被广泛采纳。
• 探究普通个体（而非高地位或人脉广泛者）在发起和传播语言变革中的作用。
• 建模社交网络中模仿与决策行为的动态过程，重点关注个体如何形成对他人言语的心理表征。
• 探索信息级联导致创新广泛采纳的条件，尤其是在缺乏自上而下影响的情况下。
• 挑战‘唯有影响力人物或广播媒体推动社会变革’的假设，特别是在语言领域。

提出的方法

• 该模型采用一种新颖的决策函数，介于概率匹配（匹配观察到的频率）与规则化（使某些形式比频率建议的更常出现）之间。
• 使用蒙特卡洛模拟，探索规则化强度、个体偏差分布与网络位置之间的相互作用。
• 网络结构被建模为社交图，个体通过与邻居的交流来更新其语言行为。
• 分析两种决策模式：'分类'（高规则化，低温决策规则）与'概率'（低规则化，高温规则）。
• 模型追踪创新在社交网络中的传播，测量在不同条件下的采纳率与级联形成情况。
• 该框架被应用于模拟平等主义（基层驱动）与枢纽驱动（影响者主导）的变革情景。

实验结果

研究问题

• RQ1 在何种条件下，由普通个体发起的任意语言创新能够被社区广泛采纳？
• RQ2 个体决策中的规则化程度如何影响基层创新传播的可能性？
• RQ3 为何人脉广泛者尽管具有影响力，却常无法成功发起语言变革？
• RQ4 网络位置与个体偏差在语言变革信息级联形成中发挥何种作用？
• RQ5 社会团结感，而非地位或声望，能否解释基层语言创新的采纳？

主要发现

• 在适度规则化水平下，既无高中心性也无高地位的普通个体最有可能发起能广泛传播的创新。
• 信息级联可在不依赖高度连接个体或广播媒体的情况下形成，支持基层变革的可行性。
• 高度连接的个体往往更保守，因其从众多来源接收信号，从而降低了其发起变革的可能性。
• 模型表明，即使创新者处于孤立状态，只要其周围有一批具有正向偏差的个体，创新仍可获得立足点并传播开来。
• 分类决策规则（高规则化）会导致快速而彻底的变革，且更受人脉广泛少数群体青睐，但该模式并不代表典型语言演变。
• 结果支持社会团结感而非隐性声望或地位，是基层语言创新采纳的主导因素这一观点。