The Relationship Between Linguistic Features and Psychological States: A Quantitative Approach
Main Article Content
Abstract
Linguistic features are crucial in identifying psychological states. Prior studies have attempted to investigate the influence of psychological states on individual language usage through quantitative analysis, as well as which linguistic features can effectively indicate an individual’s psychological state. Conducting a systematic review of pertinent literature, this study initially outlines the linguistic features related to psychological states extracted quantitatively, encompassing three dimensions: vocabulary, syntax, and emotion. Subsequently, it summarizes the correlations between linguistic features across different levels and psychological states based on quantitative methods. Last, the limitations of existing research are discussed. This study contributes to a deeper understanding of the rationale, significance, and applicability of applying linguistic features in detecting psychological states and provides guidance for future research in this domain.
Keywords:
psychological states; linguistic features; quantitative analysis
Article Details
How to Cite
XIAOWEI, Du; XINTONG, Zhou; XIAOFEI, He.
The Relationship Between Linguistic Features and Psychological States: A Quantitative Approach.
Medical Research Archives, [S.l.], v. 12, n. 8, aug. 2024.
ISSN 2375-1924.
Available at: <https://esmed.org/MRA/mra/article/view/5685>. Date accessed: 06 sep. 2024.
doi: https://doi.org/10.18103/mra.v12i8.5685.
Section
Research Articles
The Medical Research Archives grants authors the right to publish and reproduce the unrevised contribution in whole or in part at any time and in any form for any scholarly non-commercial purpose with the condition that all publications of the contribution include a full citation to the journal as published by the Medical Research Archives.
References
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https://doi.org/10.1016/j.jcomdis.2022.106298.
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[23] DEMIRAY Ç K & GENÇÖZ T. Linguistic reflections on psychotherapy：Change in usage of the first person pronoun in information structure positions [J]. Journal of Psycholinguistic Research, 2018, 47(4):959–973.
https://doi.org/10.1007/s10936-018-9569-4.
[24] DESMET B & HOSTE V. Emotion detection in suicide notes [J]. Expert Systems with Applications, 2013, 40(16):6351–6358. https://doi.org/10.1016/j.eswa.2013.05.050.
[25] DU，X. Lexical Features and psychological states: A quantitative linguistic approach [J]. Journal of Quantitative Linguistics, 2023,1-23. https://doi.org/10.1080/09296174.2023.2256211.
[26] DU X, SUN Y. Linguistic features and psychological states：A machine-learning based approach [J]. Frontiers in Psychology, 2022, 12.
[27] EICHSTAEDT J C, SMITH R J, MERCHANT R M, et al. Facebook language predicts depression in medical records [A]. Proceedings of the National Academy of Sciences [C], 2018, 115(44):11203-11208. https://doi.org/10.1073/pnas.1802331115.
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[30] HANDELMAN L D & LESTER D. The content of suicide notes from attempters and completers [J]. Crisis, 2007, 28(2):102-104. https://doi.org/10.1027/0227-5910.28.2.102.
[31] HOLMES D, ALPERS G W, ISMAILJI T, et al. Cognitive and emotional processing in narratives of women abused by intimate partners [J]. Violence Against Women, 2007, 13(11): 1192-1205.
https://doi.org/10.1177/1077801207307801.
[32] HOMAN C, JOHAR R, LIU T, et al. Toward macro-insights for suicide prevention: Analyzing fine-grained distress at scale [A]. In P. Resnik, R. Resnik & M. Mitchell (Eds.), Proceedings of the Workshop on Computational Linguistics and Clinical Psychology: From Linguistic Signal to Clinical Reality (pp. 107-117) [C]. Association for Computational Linguistics. 2014. https://doi.org/10.3115/v1/W14-3213.
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