A Collection of Swedish Diachronic Word Embedding Models Trained on Historical Newspaper Data | Zendy

Simon Hengchen | Zendy; Nina Tahmasebi | Zendy

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A Collection of Swedish Diachronic Word Embedding Models Trained on Historical Newspaper Data

Author(s) -

Simon Hengchen,

Nina Tahmasebi

Publication year - 2021

Publication title -

journal of open humanities data

Language(s) - English

Resource type - Journals

ISSN - 2059-481X

DOI - 10.5334/johd.22

Subject(s) - newspaper , natural language processing , word embedding , computer science , word (group theory) , context (archaeology) , artificial intelligence , linguistics , embedding , data collection , corpus linguistics , history , sociology , media studies , social science , philosophy , archaeology

This paper describes the creation of several word embedding models based on a large collection of diachronic Swedish newspaper material available through Sprakbanken Text, the Swedish language bank. This data was produced in the context of Sprakbanken Text’s continued mission to collaborate with humanities and natural language processing (NLP) researchers and to provide freely available language resources, for the development of state-of-the-art NLP methods and tools.

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