Unlocking the Digitized Historical Newspaper Archive Exploring Historical Insights with Deep Learning

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Publicado en:Information Technology and Libraries (Online) vol. 44, no. 3 (Sep 2025), p. 1-17
Autor principal: Lum, Vincent Wai-Yip
Otros Autores: Yip, Michael Kin-Fu
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American Library Association
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024 7 |a 10.5860/ital.v44i3.17292  |2 doi 
035 |a 3255486853 
045 2 |b d20250901  |b d20250930 
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100 1 |a Lum, Vincent Wai-Yip  |u Digital Technologies Librarian, The Chinese University of Hong Kong 
245 1 |a Unlocking the Digitized Historical Newspaper Archive Exploring Historical Insights with Deep Learning 
260 |b American Library Association  |c Sep 2025 
513 |a Journal Article 
520 3 |a This paper aims to utilize historical newspapers through the application of computer vision and machine/deep learning to extract the headlines and illustrations from newspapers for storytelling. This endeavor seeks to unlock the historical knowledge embedded within newspaper contents while simultaneously utilizing cutting-edge methodological paradigms for research in the digital humanities (DH) realm. We targeted to provide another facet apart from the traditional search or browse interfaces and incorporated those DH tools with place- and time-based visualizations. Experimental results showed our proposed methodologies in OCR (optical character recognition) with scraping and deep learning object detection models can be used to extract the necessary textual and image content for more sophisticated analysis. Timeline and geodata visualization products were developed to facilitate a comprehensive exploration of our historical newspaper data. The timeline-based tool spanned the period from July 1942 to July 1945, enabling users to explore the evolving narratives through the lens of daily headlines. The interactive geographical tool can enable users to identify geographic hotspots and patterns. Combining both products can enrich users' understanding of the events and narratives unfolding across time and space. 
651 4 |a Hong Kong China 
651 4 |a China 
653 |a Software 
653 |a Datasets 
653 |a Deep learning 
653 |a Newspapers 
653 |a Optical character recognition 
653 |a Narratives 
653 |a Computer vision 
653 |a Visualization 
653 |a Geography 
653 |a Text analysis 
653 |a Empowerment 
653 |a Propaganda 
653 |a Digitization 
653 |a Algorithms 
653 |a Object recognition 
653 |a Digital humanities 
653 |a Ideograph recognition 
653 |a Storytelling 
653 |a Humanities 
653 |a Human-computer interaction 
653 |a Learning 
653 |a Interfaces 
653 |a Methodological approaches 
653 |a Journalism 
653 |a War 
653 |a Character Recognition 
653 |a Researchers 
653 |a Electronic Equipment 
653 |a Time 
653 |a Language Processing 
653 |a Data Processing 
653 |a Computer Software 
653 |a Story Telling 
700 1 |a Yip, Michael Kin-Fu  |u Collection and Programme Support Librarian, The Hang Seng University of Hong Kong Library. O 2025. 
773 0 |t Information Technology and Libraries (Online)  |g vol. 44, no. 3 (Sep 2025), p. 1-17 
786 0 |d ProQuest  |t ABI/INFORM Global 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3255486853/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch 
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