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Psychiatry on Twitter: Content Analysis of the Use of Psychiatric Terms in French
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In: ISSN: 2561-326X ; JMIR Formative Research ; https://hal.archives-ouvertes.fr/hal-03614832 ; JMIR Formative Research, JMIR Publications 2022, 6 (2), pp.e18539. ⟨10.2196/18539⟩ ; https://formative.jmir.org/2022/2/e18539 (2022)
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Psychological Well-Being of Left-Behind Children in China: Text Mining of the Social Media Website Zhihu.
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In: International journal of environmental research and public health, vol 19, iss 4 (2022)
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Abstract:
China's migrant population has significantly contributed to its economic growth; however, the impact on the well-being of left-behind children (LBC) has become a serious public health problem. Text mining is an effective tool for identifying people's mental state, and is therefore beneficial in exploring the psychological mindset of LBC. Traditional data collection methods, which use questionnaires and standardized scales, are limited by their sample sizes. In this study, we created a computational application to quantitively collect personal narrative texts posted by LBC on Zhihu, which is a Chinese question-and-answer online community website; 1475 personal narrative texts posted by LBC were gathered. We used four types of words, i.e., first-person singular pronouns, negative words, past tense verbs, and death-related words, all of which have been associated with depression and suicidal ideations in the Chinese Linguistic Inquiry Word Count (CLIWC) dictionary. We conducted vocabulary statistics on the personal narrative texts of LBC, and bilateral t-tests, with a control group, to analyze the psychological well-being of LBC. The results showed that the proportion of words related to depression and suicidal ideations in the texts of LBC was significantly higher than in the control group. The differences, with respect to the four word types (i.e., first-person singular pronouns, negative words, past tense verbs, and death-related words), were 5.37, 2.99, 2.65, and 2.00 times, respectively, suggesting that LBC are at a higher risk of depression and suicide than their counterparts. By sorting the texts of LBC, this research also found that child neglect is a main contributing factor to psychological difficulties of LBC. Furthermore, mental health problems and the risk of suicide in vulnerable groups, such as LBC, is a global public health issue, as well as an important research topic in the era of digital public health. Through a linguistic analysis, the results of this study confirmed that the experiences of left-behind children negatively impact their mental health. The present findings suggest that it is vital for the public and nonprofit sectors to establish online suicide prevention and intervention systems to improve the well-being of LBC through digital technology.
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Keyword:
Behavioral and Social Science; Clinical Research; Depression; left-behind children; linguistic analysis; Mental Health; personal narrative text; Prevention; psychological well-being; Suicide; text mining; textual analysis; Toxicology
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URL: https://escholarship.org/uc/item/74g2z1q0
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VEREINDEUTIGUNG ZUR KLASSIFIZIERUNG LEXIKALISCHER OBJEKTE ; DISAMBIGUATION FOR THE CLASSIFICATION OF LEXICAL ITEMS ; DÉSAMBÏGUISATION POUR LA CLASSIFICATION DE LEXÈMES
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In: https://hal.archives-ouvertes.fr/hal-03598242 ; France, Patent n° : EP3937059A1. 2022 (2022)
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PROTECT: A Pipeline for Propaganda Detection and Classification
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In: CLiC-it 2021- Italian Conference on Computational Linguistics ; https://hal.archives-ouvertes.fr/hal-03417019 ; CLiC-it 2021- Italian Conference on Computational Linguistics, Jan 2022, Milan, Italy (2022)
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Linguistic intergroup bias and persistence of stereotype-affirming memory ...
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Linguistic intergroup bias and persistence of stereotype-affirming memory - Addendum 04.26.2022 ...
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Evaluation computergestützter Verfahren der Emotionsklassifikation für deutschsprachige Dramen um 1800 ...
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Evaluation computergestützter Verfahren der Emotionsklassifikation für deutschsprachige Dramen um 1800 ...
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“Thou Shalt Not Take the Lord’s Name in Vain”: A Methodological Proposal to Identify Religious Hate Content on Digital Social Networks
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In: International Journal of Communication; Vol 16 (2022); 22 ; 1932-8036 (2022)
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What was Theoretical Biology? A Topic-Modelling Analysis of a Multilingual Corpus of Monographs and Journals, 1914-1945 ...
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What was Theoretical Biology? A Topic-Modelling Analysis of a Multilingual Corpus of Monographs and Journals, 1914-1945 ...
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What was Theoretical Biology? A Topic-Modelling Analysis of a Multilingual Corpus of Monographs and Journals, 1914-1945 ...
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What was Theoretical Biology? A Topic-Modelling Analysis of a Multilingual Corpus of Monographs and Journals, 1914-1945 ...
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АРТИКУЛЯЦИОННЫЙ МЕТОД ФОНЕТИКИ В СООТНОШЕНИИ «ЧАСТЬ – ЦЕЛОЕ» ... : ARTICULATION METHOD OF PHONETICS IN THE RATIO "PART WHOLE" ...
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ЗНАЧЕНИЕ НАУЧНО-ПОПУЛЯРНОЙ СТАТЬИ ... : THE IMPORTANCE OF A POPULAR SCIENTIFIC ARTICLE ...
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Кузибаева, Р.Ш.. - : Oriental renaissance: Innovative, educational, natural and social sciences, 2022
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Connecting Text Classification with Image Classification: A New Preprocessing Method for Implicit Sentiment Text Classification
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In: Sensors; Volume 22; Issue 5; Pages: 1899 (2022)
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Short Text Aspect-Based Sentiment Analysis Based on CNN + BiGRU
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In: Applied Sciences; Volume 12; Issue 5; Pages: 2707 (2022)
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