Visualisation Methods for Diachronic Semantic Shift

Raef Kazi; Alessandra Amato; Shenghui Wang; Doina Bucur

Visualisation Methods for Diachronic Semantic Shift

Raef Kazi, Alessandra Amato, Shenghui Wang, Doina Bucur

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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Abstract

The meaning and usage of a concept or a word changes over time. These diachronic semantic shifts reflect the change of societal and cultural consensus as well as the evolution of science. The availability of large-scale corpora and recent success in language models have enabled researchers to analyse semantic shifts in great detail. However, current research lacks intuitive ways of presenting diachronic semantic shifts and making them comprehensive. In this paper, we study the PubMed dataset and compute semantic shifts across six decades. We develop three visualisation methods that can show, given a root word: the temporal change in its linguistic context, word re-occurrence, degree of similarity, time continuity, and separate trends per publisher location. We also propose a taxonomy that classifies visualisation methods for diachronic semantic shifts with respect to different purposes.

Original language	English
Title of host publication	Proceedings of the Third Workshop on Scholarly Document Processing
Publisher	Association for Computational Linguistics (ACL)
Pages	89-94
Number of pages	6
Publication status	Published - 17 Oct 2022
Event	3rd Workshop on Scholarly Document Processing, SDP 2022 - Gyeongju, Korea, Republic of Duration: 17 Oct 2022 → 17 Oct 2022 Conference number: 3 https://sdproc.org/2022/

Workshop

Workshop	3rd Workshop on Scholarly Document Processing, SDP 2022
Abbreviated title	SDP 2022
Country/Territory	Korea, Republic of
City	Gyeongju
Period	17/10/22 → 17/10/22
Other	to be held at COLING 2022 (October 12-17, 2022)
Internet address	https://sdproc.org/2022/

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2022.sdp-1.10Final published version, 1.89 MBLicence: CC BY

https://aclanthology.org/2022.sdp-1.10Licence: CC BY

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@inproceedings{3cb325b9e6d74d028c019128c11ec2bc,

title = "Visualisation Methods for Diachronic Semantic Shift",

abstract = "The meaning and usage of a concept or a word changes over time. These diachronic semantic shifts reflect the change of societal and cultural consensus as well as the evolution of science. The availability of large-scale corpora and recent success in language models have enabled researchers to analyse semantic shifts in great detail. However, current research lacks intuitive ways of presenting diachronic semantic shifts and making them comprehensive. In this paper, we study the PubMed dataset and compute semantic shifts across six decades. We develop three visualisation methods that can show, given a root word: the temporal change in its linguistic context, word re-occurrence, degree of similarity, time continuity, and separate trends per publisher location. We also propose a taxonomy that classifies visualisation methods for diachronic semantic shifts with respect to different purposes.",

author = "Raef Kazi and Alessandra Amato and Shenghui Wang and Doina Bucur",

year = "2022",

month = oct,

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language = "English",

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booktitle = "Proceedings of the Third Workshop on Scholarly Document Processing",

publisher = "Association for Computational Linguistics (ACL)",

address = "United States",

note = "3rd Workshop on Scholarly Document Processing, SDP 2022, SDP 2022 ; Conference date: 17-10-2022 Through 17-10-2022",

url = "https://sdproc.org/2022/",

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TY - GEN

T1 - Visualisation Methods for Diachronic Semantic Shift

AU - Kazi, Raef

AU - Amato, Alessandra

AU - Wang, Shenghui

AU - Bucur, Doina

N1 - Conference code: 3

PY - 2022/10/17

Y1 - 2022/10/17

N2 - The meaning and usage of a concept or a word changes over time. These diachronic semantic shifts reflect the change of societal and cultural consensus as well as the evolution of science. The availability of large-scale corpora and recent success in language models have enabled researchers to analyse semantic shifts in great detail. However, current research lacks intuitive ways of presenting diachronic semantic shifts and making them comprehensive. In this paper, we study the PubMed dataset and compute semantic shifts across six decades. We develop three visualisation methods that can show, given a root word: the temporal change in its linguistic context, word re-occurrence, degree of similarity, time continuity, and separate trends per publisher location. We also propose a taxonomy that classifies visualisation methods for diachronic semantic shifts with respect to different purposes.

AB - The meaning and usage of a concept or a word changes over time. These diachronic semantic shifts reflect the change of societal and cultural consensus as well as the evolution of science. The availability of large-scale corpora and recent success in language models have enabled researchers to analyse semantic shifts in great detail. However, current research lacks intuitive ways of presenting diachronic semantic shifts and making them comprehensive. In this paper, we study the PubMed dataset and compute semantic shifts across six decades. We develop three visualisation methods that can show, given a root word: the temporal change in its linguistic context, word re-occurrence, degree of similarity, time continuity, and separate trends per publisher location. We also propose a taxonomy that classifies visualisation methods for diachronic semantic shifts with respect to different purposes.

M3 - Conference contribution

SP - 89

EP - 94

BT - Proceedings of the Third Workshop on Scholarly Document Processing

PB - Association for Computational Linguistics (ACL)

T2 - 3rd Workshop on Scholarly Document Processing, SDP 2022

Y2 - 17 October 2022 through 17 October 2022

ER -

Visualisation Methods for Diachronic Semantic Shift

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