arXiv cs.CL· Dario Zarcone, Salvatore Miccich\`e, David Sanchez·· 12 小时前AI 评分21
用复杂系统方法检测意大利媒体的历史转折点：基于《La Repubblica》历时新闻语料的分析
Detecting Historical Turning Points in Italian Media: A Complex Systems Approach to a Diachronic News Corpus
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研究重建了意大利《La Repubblica》1985年1月1日至2000年12月31日约60万篇文章的历时语料，结合NLP与复杂系统、统计物理方法追踪媒体话语变迁。词频呈爆发式、Fano因子重尾分布且跨时间尺度稳健，词显著性与语义相似度的变点可在无先验标注下识别第一共和国向第二共和国过渡、海湾战争、科索沃战争等转折期。战争时期语义空间熵更低，表明话语更集中。
正文 · 原文
Abstract:Introduction: The increasing availability of large-scale textual corpora has opened new possibilities for data-driven, quantitative approaches to historical analysis using Natural Language Processing (NLP). However, diachronic corpora with historical relevance from the pre-digital era remain scarce and often incomplete.
Methods: We present a quantitative approach to historical analysis based on the reconstruction and exploration of a diachronic corpus of around 600,000 articles from the Italian newspaper "La Repubblica", covering all the articles published from the first of January 1985 to the 31st of December 2000 - a period of major political, social, and geopolitical change in Italy and globally. Using NLP techniques, we analyze the text at both lexical and semantic levels; we then apply tools from complex systems and statistical physics to trace shifts in media discourse over time.
Results: The word usage in the corpus is bursty, with a heavy-tailed distribution of Fano factors that is robust across timescales. Changepoints in word salience and the block structure of semantic similarity allow us to detect key transition periods, such as the transition from the First Republic to the Second Republic in Italy, or major international conflicts like the Gulf War or the Kosovo War, without relying on prior labeling. Periods of war correspond to lower entropy in the semantic space, indicating a more focused discourse.
Discussion: The results show how combining computational linguistics with ideas from complex systems can offer new quantitative insight into historical changes, opening up new paths for studying the dynamics of media and society through large-scale textual data.
| Comments: | 18 pages, 9 figures, 1 table |
| Subjects: | Physics and Society (physics.soc-ph); Statistical Mechanics (cond-mat.stat-mech); Computation and Language (cs.CL) |
| Cite as: | arXiv:2606.14348 [physics.soc-ph] |
| (or arXiv:2606.14348v2 [physics.soc-ph] for this version) | |
| https://doi.org/10.48550/arXiv.2606.14348 arXiv-issued DOI via DataCite |
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| Journal reference: | Frontiers in Complex Systems. Volume 4 (2026) 1868587 |
| Related DOI: | https://doi.org/10.3389/fcpxs.2026.1868587
DOI(s) linking to related resources |
Submission history
From: Dario Zarcone [view email]
[v1]
Fri, 12 Jun 2026 11:02:34 UTC (1,181 KB)
[v2]
Mon, 2 Nov 2026 15:35:04 UTC (1,157 KB)
来源：arXiv cs.CL · arxiv.org