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A Study on Word2Vec on a Historical Swedish Newspaper Corpus

Conference paper
Authors Nina Tahmasebi
Published in CEUR Workshop Proceedings. Vol. 2084. Proceedings of the Digital Humanities in the Nordic Countries 3rd Conference, Helsinki Finland, March 7-9, 2018. Edited by Eetu Mäkelä, Mikko Tolonen, Jouni Tuominen
Publisher University of Helsinki, Faculty of Arts
Place of publication Helsinki
Publication year 2018
Published at Department of Literature, History of Ideas, and Religion
Language en
Subject categories Data processing, Language Technology (Computational Linguistics)


Detecting word sense changes can be of great interest in the field of digital humanities. Thus far, most investigations and automatic methods have been developed and carried out on English text and most recent methods make use of word embeddings. This paper presents a study on using Word2Vec, a neural word embedding method, on a Swedish historical newspaper collection. Our study includes a set of 11 words and our focus is the quality and stability of the word vectors over time. We investigate if a word embedding method like Word2Vec can be effectively used on texts where the volume and quality is limited.

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