TY - GEN
T1 - “Vaderland”, “Volk” and “Natie”
T2 - 3rd International Workshop on Computational Approaches to Historical Language Change, LChange 2022
AU - Timmermans, Marije
AU - Vanmassenhove, Eva
AU - Shterionov, Dimitar
N1 - Publisher Copyright:
© 2022 Association for Computational Linguistics.
PY - 2022
Y1 - 2022
N2 - Languages can respond to external events in various ways - the creation of new words or named entities, additional senses might develop for already existing words or the valence of words can change. In this work, we explore the semantic shift of the Dutch words “natie” (“nation”), “volk” (“people”) and “vaderland” (“fatherland”) over a period that is known for the rise of nationalism in Europe: 1700-1880 (Jensen, 2016). The semantic change is measured by means of Dynamic Bernoulli Word Embeddings (Rudolph and Blei, 2018) which allow for comparison between word embeddings over different time slices. The word embeddings were generated based on Dutch fiction literature divided over different decades. From the analysis of the absolute drifts, it appears that the word “natie” underwent a relatively small drift. However, the drifts of “vaderland” and “volk” show multiple peaks, culminating around the turn of the nineteenth century. To verify whether this semantic change can indeed be attributed to nationalistic movements, a detailed analysis of the nearest neighbours of the target words is provided. From the analysis, it appears that “natie”, “volk” and “vaderland” became more nationalistically-loaded over time.
AB - Languages can respond to external events in various ways - the creation of new words or named entities, additional senses might develop for already existing words or the valence of words can change. In this work, we explore the semantic shift of the Dutch words “natie” (“nation”), “volk” (“people”) and “vaderland” (“fatherland”) over a period that is known for the rise of nationalism in Europe: 1700-1880 (Jensen, 2016). The semantic change is measured by means of Dynamic Bernoulli Word Embeddings (Rudolph and Blei, 2018) which allow for comparison between word embeddings over different time slices. The word embeddings were generated based on Dutch fiction literature divided over different decades. From the analysis of the absolute drifts, it appears that the word “natie” underwent a relatively small drift. However, the drifts of “vaderland” and “volk” show multiple peaks, culminating around the turn of the nineteenth century. To verify whether this semantic change can indeed be attributed to nationalistic movements, a detailed analysis of the nearest neighbours of the target words is provided. From the analysis, it appears that “natie”, “volk” and “vaderland” became more nationalistically-loaded over time.
UR - http://www.scopus.com/inward/record.url?scp=85137445412&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85137445412
VL - 3
T3 - LChange 2022 - 3rd International Workshop on Computational Approaches to Historical Language Change 2022, Proceedings of the Workshop
SP - 125
EP - 130
BT - LChange 2022
A2 - Tahmasebi, Nina
A2 - Montariol, Syrielle
A2 - Kutuzov, Andrey
A2 - Hengchen, Simon
A2 - Dubossarsky, Haim
A2 - Borin, Lars
PB - Association for Computational Linguistics (ACL)
Y2 - 26 May 2022 through 27 May 2022
ER -