This paper addresses methodological issues in diachronic data analysis for historical research. We apply two families of topic models (LDA and DTM) on a relatively large set of historical newspapers, with the aim of capturing and understanding discourse dynamics. Our case study focuses on newspapers and periodicals published in Finland between 1854 and 1917, but our method can easily be transposed to any diachronic data. Our main contributions are a) a combined sampling, training and inference procedure for applying topic models to huge and imbalanced diachronic text collections; b) a discussion on the differences between two topic models for this type of data; c) quantifying topic prominence for a period and thus a generalization of document-wise topic assignment to a discourse level; and d) a discussion of the role of humanistic interpretation with regard to analysing discourse dynamics through topic models.
Automating Historical Insight Extraction from Large-Scale Newspaper Archives via Neural Topic Modeling
Department of Computer Science , University of Luxembourg , 2, place de l’Université , 4365 , Esch-Belval Esch-sur-Alzette , Luxembourg；Centre for Contemporary \& Digital History (C 2 DH) , University of Luxembourg , 11 Porte des Sciences , 4366 , Esch-Belval Esch-sur-Alzette , Luxembourg
Lund University（隆德大学）；University of Copenhagen（哥本哈根大学）
This study compares the media discourses about Euroscepticism in 2014 across six countries (United Kingdom, Ireland, France, Spain, Sweden, and Denmark). We assess the extent to which the mass media's reporting of Euroscepticism indicates the Europeanization of public spheres. Using a mixed-methods approach combining LDA topic modeling and qualitative coding, we find that approximately 70 per cent of print articles mentioning "Euroscepticism" or "Eurosceptic" are framed in a non-domestic (i.e. European) context. In five of the six cases studied, articles exhibiting a European context are strik…
University of Bremen（不来梅大学）；University of Stuttgart（斯图加特大学）
Newspaper reports provide a rich source of information on the unfolding of public debate on specific policy fields that can serve as basis for inquiry in political science. Such debates are often triggered by critical events, which attract public attention and incite the reactions of political actors: crisis sparks the debate. However, due to the challenges of reliable annotation and modeling, few large-scale datasets with high-quality annotation are available. This paper introduces DebateNet2.0, which traces the political discourse on the European refugee crisis in the German quality newspape…
Approaches to Analysing Historical Newspapers Using LLMs
Institute of Contemporary History（当代史研究所）；Faculty of Arts, University of Ljubljana（卢布尔雅那大学文学院）；Faculty of Computer Science, University of Ljubljana（卢布尔雅那大学计算机科学学院）
Old Content and Modern Tools - Searching Named Entities in a Finnish OCRed Historical Newspaper Collection 1771-1910
National Library of Finland, Centre for Preservation and Digitization（芬兰国家图书馆，保存与数字化中心）；Aalto University, Semantic Computing Research Group（阿尔托大学，语义计算研究组）；University of Helsinki, Department of Modern Languages（赫尔辛基大学，现代语言系）；Department of Linguistics and English Language, Lancaster University（兰卡斯特大学，语言学与英语语言系）
University of Eastern Finland（东芬兰大学）；Tampere University（坦佩雷大学）；University of Helsinki（赫尔辛基大学）；The National Library of Finland（芬兰国家图书馆）
Introduction. We study effect of different quality optical character recognition in interactive information retrieval with a collection of one digitized historical Finnish newspaper. Method. This study is based on the simulated interactive information retrieval work task model. Thirty-two users made searches to an article collection of Finnish newspaper Uusi Suometar 1869-1918 with ca. 1.45 million auto segmented articles. Our article search database had two versions of each article with different quality optical character recognition. Each user performed six pre-formulated and six self-formul…
The National Library of Finland has digitized the historical newspapers published in Finland between 1771 and 1910. This collection contains approximately 1.95 million pages in Finnish and Swedish. Finnish part of the collection consists of about 2.40 billion words. The National Library's Digital Collections are offered via the digi.kansalliskirjasto.fi web service, also known as Digi. Part of the newspaper material (from 1771 to 1874) is also available freely downloadable in The Language Bank of Finland provided by the FINCLARIN consortium. The collection can also be accessed through the Korp…
Processing the structure of documents: Logical Layout Analysis of historical newspapers in French
Centre de Recherches Interdisciplinaires et Transculturelles (CRIT)（跨学科与跨文化研究中心（CRIT））；Université de Bourgogne Franche-Comté（勃艮第-弗朗什-孔泰大学）；Institut Universitaire de France (IUF)（法国大学研究院（IUF））
University of Eastern Finland（东芬兰大学）；Tampere University（坦佩雷大学）；University of Helsinki（赫尔辛基大学）
Effects of Optical Character Recognition (OCR) quality on historical information retrieval have so far been studied in data-oriented scenarios regarding the effectiveness of retrieval results. Such studies have either focused on the effects of artificially degraded OCR quality (see, e.g., [1-2]) or utilized test collections containing texts based on authentic low quality OCR data (see, e.g., [3]). In this paper the effects of OCR quality are studied in a user-oriented information retrieval setting. Thirty-two users evaluated subjectively query results of six topics each (out of 30 topics) base…
American Stories: A Large-Scale Structured Text Dataset of Historical U.S. Newspapers
Harvard University（哈佛大学）；Massachusetts Institute of Technology（麻省理工学院）；Princeton University（普林斯顿大学）；National Bureau of Economic Research（美国国家经济研究局）；New York University（纽约大学）；Northwestern University（西北大学）
Identifying Narrative Patterns and Outliers in Holocaust Testimonies Using Topic Modeling
Hebrew University of Jerusalem（耶路撒冷希伯来大学）；Department of Computer Science（计算机科学系）；Faculty of Law and Digital Humanities（法律与数字人文学院）；Department of Communication and Journalism（传播与新闻系）
Detecting Historical Turning Points in Italian Media: A Complex Systems Approach to a Diachronic News Corpus
Department of Physics and Chemistry, University of Palermo（帕尔米洛大学物理与化学系）；Institute for Cross-Disciplinary Physics and Complex Systems (IFISC), UIB-CSIC（跨学科物理与复杂系统研究所（IFISC）， UIB-CSIC）
Stockholm University（斯德哥尔摩大学）；Athens University of Economics & Business（雅典经济与商业大学）
Large, diachronic datasets of political discourse are hard to come across, especially for resource-lean languages such as Greek. In this paper, we introduce a curated dataset of the Greek Parliament Proceedings that extends chronologically from 1989 up to 2020. It consists of more than 1 million speeches with extensive metadata, extracted from 5,355 parliamentary record files. We explain how it was constructed and the challenges that we had to overcome. The dataset can be used for both computational linguistics and political analysis-ideally, combining the two. We present such an application, …
