@inproceedings{baes-etal-2023-semantic-shifts,
title = "Semantic Shifts in Mental Health-Related Concepts",
author = "Baes, Naomi and
Haslam, Nick and
Vylomova, Ekaterina",
editor = "Tahmasebi, Nina and
Montariol, Syrielle and
Dubossarsky, Haim and
Kutuzov, Andrey and
Hengchen, Simon and
Alfter, David and
Periti, Francesco and
Cassotti, Pierluigi",
booktitle = "Proceedings of the 4th Workshop on Computational Approaches to Historical Language Change",
month = dec,
year = "2023",
address = "Singapore",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.lchange-1.13/",
doi = "10.18653/v1/2023.lchange-1.13",
pages = "119--128",
abstract = "The present study evaluates semantic shifts in mental health-related concepts in two diachronic corpora spanning 1970-2016, one academic and one general. It evaluates whether their meanings have broadened to encompass less severe phenomena and whether they have become more pathology related. It applies a recently proposed methodology (Baes et al., 2023) to examine whether words collocating with a sample of mental health concepts have become less emotionally intense and develops a new way to examine whether the concepts increasingly co-occur with pathology-related terms. In support of the first hypothesis, mental health-related concepts became associated with less emotionally intense language in the psychology corpus (addiction, anger, stress, worry) and in the general corpus (addiction, grief, stress, worry). In support of the second hypothesis, mental health-related concepts came to be more associated with pathology-related language in psychology (addiction, grief, stress, worry) and in the general corpus (grief, stress). Findings demonstrate that some mental health concepts have become normalized and/or pathologized, a conclusion with important social and cultural implications."
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%0 Conference Proceedings
%T Semantic Shifts in Mental Health-Related Concepts
%A Baes, Naomi
%A Haslam, Nick
%A Vylomova, Ekaterina
%Y Tahmasebi, Nina
%Y Montariol, Syrielle
%Y Dubossarsky, Haim
%Y Kutuzov, Andrey
%Y Hengchen, Simon
%Y Alfter, David
%Y Periti, Francesco
%Y Cassotti, Pierluigi
%S Proceedings of the 4th Workshop on Computational Approaches to Historical Language Change
%D 2023
%8 December
%I Association for Computational Linguistics
%C Singapore
%F baes-etal-2023-semantic-shifts
%X The present study evaluates semantic shifts in mental health-related concepts in two diachronic corpora spanning 1970-2016, one academic and one general. It evaluates whether their meanings have broadened to encompass less severe phenomena and whether they have become more pathology related. It applies a recently proposed methodology (Baes et al., 2023) to examine whether words collocating with a sample of mental health concepts have become less emotionally intense and develops a new way to examine whether the concepts increasingly co-occur with pathology-related terms. In support of the first hypothesis, mental health-related concepts became associated with less emotionally intense language in the psychology corpus (addiction, anger, stress, worry) and in the general corpus (addiction, grief, stress, worry). In support of the second hypothesis, mental health-related concepts came to be more associated with pathology-related language in psychology (addiction, grief, stress, worry) and in the general corpus (grief, stress). Findings demonstrate that some mental health concepts have become normalized and/or pathologized, a conclusion with important social and cultural implications.
%R 10.18653/v1/2023.lchange-1.13
%U https://aclanthology.org/2023.lchange-1.13/
%U https://doi.org/10.18653/v1/2023.lchange-1.13
%P 119-128
Markdown (Informal)
[Semantic Shifts in Mental Health-Related Concepts](https://aclanthology.org/2023.lchange-1.13/) (Baes et al., LChange 2023)
ACL
- Naomi Baes, Nick Haslam, and Ekaterina Vylomova. 2023. Semantic Shifts in Mental Health-Related Concepts. In Proceedings of the 4th Workshop on Computational Approaches to Historical Language Change, pages 119–128, Singapore. Association for Computational Linguistics.