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Navigating the Mise-en-Page: Interpretive Machine Learning Approaches to the Visual Layouts of Multi-Ethnic Periodicals
arXiv - CS - Digital Libraries Pub Date : 2021-09-03 , DOI: arxiv-2109.01732
Benjamin Charles Germain Lee, Joshua Ortiz Baco, Sarah H. Salter, Jim Casey

This paper presents a computational method of analysis that draws from machine learning, library science, and literary studies to map the visual layouts of multi-ethnic newspapers from the late 19th and early 20th century United States. This work departs from prior approaches to newspapers that focus on individual pieces of textual and visual content. Our method combines Chronicling America's MARC data and the Newspaper Navigator machine learning dataset to identify the visual patterns of newspaper page layouts. By analyzing high-dimensional visual similarity, we aim to better understand how editors spoke and protested through the layout of their papers.

中文翻译:

导航 Mise-en-Page:多民族期刊视觉布局的解释性机器学习方法

本文提出了一种计算分析方法,该方法借鉴了机器学习、图书馆学和文学研究,以绘制 19 世纪末和 20 世纪初美国多民族报纸的视觉布局。这项工作与以前关注单个文本和视觉内容的报纸方法不同。我们的方法结合了 Chronicles America 的 MARC 数据和 Newspaper Navigator 机器学习数据集来识别报纸页面布局的视觉模式。通过分析高维视觉相似性,我们旨在更好地了解编辑如何通过他们的论文布局发表言论和抗议。
更新日期:2021-09-07
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