Laplacian U-Processes for Multiple Change-Point Detection in Dependent Text Networks: An Application to Historical Chinese Articles
Abstract
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.
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BibTeX
@misc{chen2026laplacian,
title = {{Laplacian U-Processes for Multiple Change-Point Detection in Dependent Text Networks: An Application to Historical Chinese Articles}},
author = {Fanghua Chen and Yizhou Cai and Lu zhou and Ting Fung Ma},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.19306},
eprint = {2609.19306},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.19306},
}
RIS
TY - UNPB
TI - Laplacian U-Processes for Multiple Change-Point Detection in Dependent Text Networks: An Application to Historical Chinese Articles
AU - Fanghua Chen
AU - Yizhou Cai
AU - Lu zhou
AU - Ting Fung Ma
PY - 2026
DA - 2026/09/16
PB - arXiv
DO - 10.48550/arxiv.2609.19306
UR - https://arxiv.org/abs/2609.19306
AB - 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.
ER -