Linking large digitized newspaper corpora in different languages that have become available in national and state libraries opens up new possibilities for the computational analysis of patterns of information flow across national and linguistic boundaries. The significant contribution this article presents is to demonstrate how word vector models can be used to explore the way concepts have shifted in meaning over time, as they migrated across space, by comparing newspapers from different countries published between 1840 and 1914. We define a concept, rather pragmatically, as a key term or core idea that has been used in historical discourse: an abstraction or mental representation that has served as a building block for thoughts and belief...
Our paper analyzes the historical understanding of Finland and Finnishness as it was expressed in ne...
A collection of Swedish diachronic word embedding models trained on historical newspaper data Simon...
Recently, the use of word embedding models (WEM) has received ample attention in the natural languag...
Linking large digitized newspaper corpora in different languages that have become available in natio...
peer reviewedThis study proposes an experimental method to trace the historical evolution of media d...
Nation and nationhood are among the most frequently studied concepts in the field of intellectual hi...
This paper addresses methodological issues in diachronic data analysis for historical research. We a...
This paper addresses methodological issues in diachronic data analysis for historical research. We a...
Word vectors related to the paper Machines in the media: semantic change in the lexicon of mechaniza...
Topic modelling is often described as a text-mining tool for conducting a study of hidden semantic s...
In different times, people use different words to describe concepts. Change and stability in word us...
This article aims to offer a methodological contribution to digital humanities by exploring the valu...
13 semi-structured interviews were conducted with librarians, archivists and digital content manager...
This paper is a part of a collaboration between computer scientists and historians aimed at developm...
This paper is based on the study of text reuse in the Finnish press from 1771-1920. In the Computati...
Our paper analyzes the historical understanding of Finland and Finnishness as it was expressed in ne...
A collection of Swedish diachronic word embedding models trained on historical newspaper data Simon...
Recently, the use of word embedding models (WEM) has received ample attention in the natural languag...
Linking large digitized newspaper corpora in different languages that have become available in natio...
peer reviewedThis study proposes an experimental method to trace the historical evolution of media d...
Nation and nationhood are among the most frequently studied concepts in the field of intellectual hi...
This paper addresses methodological issues in diachronic data analysis for historical research. We a...
This paper addresses methodological issues in diachronic data analysis for historical research. We a...
Word vectors related to the paper Machines in the media: semantic change in the lexicon of mechaniza...
Topic modelling is often described as a text-mining tool for conducting a study of hidden semantic s...
In different times, people use different words to describe concepts. Change and stability in word us...
This article aims to offer a methodological contribution to digital humanities by exploring the valu...
13 semi-structured interviews were conducted with librarians, archivists and digital content manager...
This paper is a part of a collaboration between computer scientists and historians aimed at developm...
This paper is based on the study of text reuse in the Finnish press from 1771-1920. In the Computati...
Our paper analyzes the historical understanding of Finland and Finnishness as it was expressed in ne...
A collection of Swedish diachronic word embedding models trained on historical newspaper data Simon...
Recently, the use of word embedding models (WEM) has received ample attention in the natural languag...