The Expressions of Depression and Anxiety in Chinese Psycho-counseling: Usage of First-person Singular Pronoun and Negative Emotional Words
- URL: http://arxiv.org/abs/2507.13839v1
- Date: Fri, 18 Jul 2025 11:53:15 GMT
- Title: The Expressions of Depression and Anxiety in Chinese Psycho-counseling: Usage of First-person Singular Pronoun and Negative Emotional Words
- Authors: Lizhi Ma, Tong Zhao, Shuai Zhang, Nirui Song, Hongliang He, Anqi Li, Ran Feng, Huachuan Qiu, Jingsong Ma, Zhenzhong Lan,
- Abstract summary: This study explores the relationship between linguistic expressions and psychological states of depression and anxiety within Chinese psycho-counseling interactions.<n>It employed a general linear mixed-effect model to assess linguistic patterns quantified by the Linguistic Inquiry and Word Count software.<n>Results indicate a significant positive correlation between the frequency of negative emotional words and the severity of both depressive and anxious states among clients.
- Score: 25.87897084393168
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: This study explores the relationship between linguistic expressions and psychological states of depression and anxiety within Chinese psycho-counseling interactions, focusing specifically on the usage of first-person singular pronouns and negative emotional words. Utilizing a corpus derived from 735 online counseling sessions, the analysis employed a general linear mixed-effect model to assess linguistic patterns quantified by the Linguistic Inquiry and Word Count (LIWC) software. Results indicate a significant positive correlation between the frequency of negative emotional words and the severity of both depressive and anxious states among clients. However, contrary to prior findings predominantly derived from English-language contexts, the usage frequency of first-person singular pronouns did not vary significantly with the clients' psychological conditions. These outcomes are discussed within the framework of cultural distinctions between collectivist Chinese contexts and individualistic Western settings, as well as the interactive dynamics unique to psycho-counseling conversations. The findings highlight the nuanced influence of cultural and conversational contexts on language use in mental health communications, providing insights into psycholinguistic markers relevant to therapeutic practices in Chinese-speaking populations.
Related papers
- Decoding Linguistic Nuances in Mental Health Text Classification Using Expressive Narrative Stories [5.091061468748012]
This study bridges the gap by focusing on Expressive Narrative Stories (ENS) from individuals with and without self-declared depression.<n>Our research evaluates the utility of advanced language models, BERT and MentalBERT, against traditional models.<n>BERT exhibited minimal sensitivity to the absence of topic words in ENS, suggesting its superior capability to understand deeper linguistic features.
arXiv Detail & Related papers (2024-12-20T19:29:21Z) - Context is Important in Depressive Language: A Study of the Interaction Between the Sentiments and Linguistic Markers in Reddit Discussions [2.6571678272335717]
This study investigates the impact of discussion topic as context on linguistic markers and emotional expression in depression.
Our sentiment analysis revealed a broader range of emotional intensity in depressed individuals, with both higher negative and positive sentiments than controls.
arXiv Detail & Related papers (2024-05-28T11:19:39Z) - Affective-NLI: Towards Accurate and Interpretable Personality Recognition in Conversation [30.820334868031537]
Personality Recognition in Conversation (PRC) aims to identify the personality traits of speakers through textual dialogue content.
We propose Affective Natural Language Inference (Affective-NLI) for accurate and interpretable PRC.
arXiv Detail & Related papers (2024-04-03T09:14:24Z) - Computational Analysis of Stress, Depression and Engagement in Mental Health: A Survey [62.31381724639944]
Stress and depression are interrelated and together they impact engagement in daily tasks.<n>This survey is the first to simultaneously explore computational methods for analyzing stress, depression and engagement.
arXiv Detail & Related papers (2024-03-09T11:16:09Z) - Language-based Valence and Arousal Expressions between the United States and China: a Cross-Cultural Examination [6.122854363918857]
This paper explores cultural differences in affective expressions by comparing Twitter/X (geolocated to the US) and Sina Weibo (in Mainland China)<n>Using the NRC-VAD lexicon to measure valence and arousal, we identify distinct patterns of emotional expression across both platforms.<n>We uncover significant cross-cultural differences in arousal, with US users displaying higher emotional intensity than Chinese users.
arXiv Detail & Related papers (2024-01-10T16:32:25Z) - Comparing Biases and the Impact of Multilingual Training across Multiple
Languages [70.84047257764405]
We present a bias analysis across Italian, Chinese, English, Hebrew, and Spanish on the downstream sentiment analysis task.
We adapt existing sentiment bias templates in English to Italian, Chinese, Hebrew, and Spanish for four attributes: race, religion, nationality, and gender.
Our results reveal similarities in bias expression such as favoritism of groups that are dominant in each language's culture.
arXiv Detail & Related papers (2023-05-18T18:15:07Z) - Information-Restricted Neural Language Models Reveal Different Brain
Regions' Sensitivity to Semantics, Syntax and Context [87.31930367845125]
We trained a lexical language model, Glove, and a supra-lexical language model, GPT-2, on a text corpus.
We then assessed to what extent these information-restricted models were able to predict the time-courses of fMRI signal of humans listening to naturalistic text.
Our analyses show that, while most brain regions involved in language are sensitive to both syntactic and semantic variables, the relative magnitudes of these effects vary a lot across these regions.
arXiv Detail & Related papers (2023-02-28T08:16:18Z) - Co-Located Human-Human Interaction Analysis using Nonverbal Cues: A
Survey [71.43956423427397]
We aim to identify the nonverbal cues and computational methodologies resulting in effective performance.
This survey differs from its counterparts by involving the widest spectrum of social phenomena and interaction settings.
Some major observations are: the most often used nonverbal cue, computational method, interaction environment, and sensing approach are speaking activity, support vector machines, and meetings composed of 3-4 persons equipped with microphones and cameras, respectively.
arXiv Detail & Related papers (2022-07-20T13:37:57Z) - Perception Point: Identifying Critical Learning Periods in Speech for
Bilingual Networks [58.24134321728942]
We compare and identify cognitive aspects on deep neural-based visual lip-reading models.
We observe a strong correlation between these theories in cognitive psychology and our unique modeling.
arXiv Detail & Related papers (2021-10-13T05:30:50Z) - Disambiguating Affective Stimulus Associations for Robot Perception and
Dialogue [67.89143112645556]
We provide a NICO robot with the ability to learn the associations between a perceived auditory stimulus and an emotional expression.
NICO is able to do this for both individual subjects and specific stimuli, with the aid of an emotion-driven dialogue system.
The robot is then able to use this information to determine a subject's enjoyment of perceived auditory stimuli in a real HRI scenario.
arXiv Detail & Related papers (2021-03-05T20:55:48Z) - Pragmatic information in translation: a corpus-based study of tense and
mood in English and German [70.3497683558609]
Grammatical tense and mood are important linguistic phenomena to consider in natural language processing (NLP) research.
We consider the correspondence between English and German tense and mood in translation.
Of particular importance is the challenge of modeling tense and mood in rule-based, phrase-based statistical and neural machine translation.
arXiv Detail & Related papers (2020-07-10T08:15:59Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.