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Main Authors: Jing, Yi, Qiu, Weiyun, Peng, Yihang, Sui, Zhifang
Format: Preprint
Published: 2026
Subjects:
Online Access:https://arxiv.org/abs/2604.11749
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author Jing, Yi
Qiu, Weiyun
Peng, Yihang
Sui, Zhifang
author_facet Jing, Yi
Qiu, Weiyun
Peng, Yihang
Sui, Zhifang
contents Language change both reflects and shapes social processes, and the semantic evolution of foundational concepts provides a measurable trace of historical and social transformation. Despite recent advances in diachronic semantics and discourse analysis, existing computational approaches often (i) concentrate on a single concept or a single corpus, making findings difficult to compare across heterogeneous sources, and (ii) remain confined to surface lexical evidence, offering insufficient computational and interpretive granularity when concepts are expressed implicitly. We propose HistLens, a unified, SAE-based framework for multi-concept, multi-corpus conceptual-history analysis. The framework decomposes concept representations into interpretable features and tracks their activation dynamics over time and across sources, yielding comparable conceptual trajectories within a shared coordinate system. Experiments on long-span press corpora show that HistLens supports cross-concept, cross-corpus computation of patterns of idea evolution and enables implicit concept computation. By bridging conceptual modeling with interpretive needs, HistLens broadens the analytical perspectives and methodological repertoire available to social science and the humanities for diachronic text analysis.
format Preprint
id arxiv_https___arxiv_org_abs_2604_11749
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle HistLens: Mapping Idea Change across Concepts and Corpora
Jing, Yi
Qiu, Weiyun
Peng, Yihang
Sui, Zhifang
Computation and Language
Language change both reflects and shapes social processes, and the semantic evolution of foundational concepts provides a measurable trace of historical and social transformation. Despite recent advances in diachronic semantics and discourse analysis, existing computational approaches often (i) concentrate on a single concept or a single corpus, making findings difficult to compare across heterogeneous sources, and (ii) remain confined to surface lexical evidence, offering insufficient computational and interpretive granularity when concepts are expressed implicitly. We propose HistLens, a unified, SAE-based framework for multi-concept, multi-corpus conceptual-history analysis. The framework decomposes concept representations into interpretable features and tracks their activation dynamics over time and across sources, yielding comparable conceptual trajectories within a shared coordinate system. Experiments on long-span press corpora show that HistLens supports cross-concept, cross-corpus computation of patterns of idea evolution and enables implicit concept computation. By bridging conceptual modeling with interpretive needs, HistLens broadens the analytical perspectives and methodological repertoire available to social science and the humanities for diachronic text analysis.
title HistLens: Mapping Idea Change across Concepts and Corpora
topic Computation and Language
url https://arxiv.org/abs/2604.11749