发表机构
University of South Carolina; Texas State University（南卡罗来纳大学; 德州州立大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
提出WCO框架检测弱相依文本网络变点，在《新青年》语料中定位1919年11月变点，与五四运动语言转型吻合。
AI 中文摘要
我们提出一个双视角加权共现算子（WCO）框架，用于弱相依文本网络中的离线变点检测。加权词共现图产生一阶直接共现和二阶共享上下文两个视角，利用从独立试点语料库学习的映射投影为成对欧几里得观测。WCO扫描检测跨视角依赖的变化。相依乘子自助法检验变点是否存在，而分段块自助法给出其位置的描述性稳定区间。我们建立了零假设弱收敛性、自助法有效性、渐近尺寸控制、在单一可识别变点下的一致性定位，以及词级误差的扰动界。CUSUM和高斯核MMD扫描提供互补基准。在1915-1921年《新青年》语料库中，该方法检测到1919年11月发生变点，描述性95%稳定区间为1919年4月至1920年6月，与围绕中国五四运动和新文化运动的语言转型一致。
英文摘要
We propose a two-view weighted-concordance operator (WCO) framework for offline change-point detection in weakly dependent text networks. Weighted word-co-occurrence graphs yield first-order direct-co-occurrence and second-order shared-context views, projected into paired Euclidean observations using maps learned from an independent pilot corpus. A WCO scan detects changes in cross-view dependence. A dependent multiplier bootstrap tests for a change, while a segment-wise block bootstrap gives a descriptive stability interval for its location. We establish null weak convergence, bootstrap validity, asymptotic size control, consistent localization under a single identifiable change, and perturbation bounds for token-level errors. CUSUM and Gaussian-kernel MMD scans provide complementary benchmarks. In the 1915-1921 New Youth corpus, the method detects a change in November 1919, with a descriptive 95 percent stability interval from April 1919 to June 1920, consistent with the linguistic transition surrounding China's May Fourth and New Culture movements.
Comments32 pages, 4 figures, and 2 tables. Supplementary material is not included
