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Mangalik S, Eichstaedt JC, Giorgi S, Mun J, Ahmed F, Gill G, V Ganesan A, Subrahmanya S, Soni N, Clouston SAP, Schwartz HA. Robust language-based mental health assessments in time and space through social media. NPJ Digit Med 2024; 7:109. [PMID: 38698174 PMCID: PMC11065872 DOI: 10.1038/s41746-024-01100-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2023] [Accepted: 04/04/2024] [Indexed: 05/05/2024] Open
Abstract
In the most comprehensive population surveys, mental health is only broadly captured through questionnaires asking about "mentally unhealthy days" or feelings of "sadness." Further, population mental health estimates are predominantly consolidated to yearly estimates at the state level, which is considerably coarser than the best estimates of physical health. Through the large-scale analysis of social media, robust estimation of population mental health is feasible at finer resolutions. In this study, we created a pipeline that used ~1 billion Tweets from 2 million geo-located users to estimate mental health levels and changes for depression and anxiety, the two leading mental health conditions. Language-based mental health assessments (LBMHAs) had substantially higher levels of reliability across space and time than available survey measures. This work presents reliable assessments of depression and anxiety down to the county-weeks level. Where surveys were available, we found moderate to strong associations between the LBMHAs and survey scores for multiple levels of granularity, from the national level down to weekly county measurements (fixed effects β = 0.34 to 1.82; p < 0.001). LBMHAs demonstrated temporal validity, showing clear absolute increases after a list of major societal events (+23% absolute change for depression assessments). LBMHAs showed improved external validity, evidenced by stronger correlations with measures of health and socioeconomic status than population surveys. This study shows that the careful aggregation of social media data yields spatiotemporal estimates of population mental health that exceed the granularity achievable by existing population surveys, and does so with generally greater reliability and validity.
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Affiliation(s)
- Siddharth Mangalik
- Department of Computer Science, Stony Brook University, Stony Brook, NY, USA.
| | - Johannes C Eichstaedt
- Department of Psychology, Stanford University, Stanford, CA, USA.
- Institute for Human-Centered A.I., Stanford University, Stanford, CA, USA.
| | - Salvatore Giorgi
- Department of Computer and Information Science, University of Pennsylvania, Philadelphia, USA
| | - Jihu Mun
- Department of Computer Science, Stony Brook University, Stony Brook, NY, USA
| | - Farhan Ahmed
- Department of Computer Science, Stony Brook University, Stony Brook, NY, USA
| | - Gilvir Gill
- Department of Computer Science, Stony Brook University, Stony Brook, NY, USA
| | - Adithya V Ganesan
- Department of Computer Science, Stony Brook University, Stony Brook, NY, USA
| | | | - Nikita Soni
- Department of Computer Science, Stony Brook University, Stony Brook, NY, USA
| | - Sean A P Clouston
- Department of Family, Population, and Preventive Medicine, Renaissance School of Medicine, Stony Brook University, Stony Brook, NY, USA
| | - H Andrew Schwartz
- Department of Computer Science, Stony Brook University, Stony Brook, NY, USA.
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Wang T, Li Q, Liu H, Shi Q, Yang F, Zhang B, Ahmed F, Jian W, Guo J. Gender difference in the relationship between personality traits and changes in depressive symptoms before and after the COVID-19 outbreak: A follow-up study among Chinese adults. J Affect Disord 2023; 326:49-56. [PMID: 36709830 PMCID: PMC9877321 DOI: 10.1016/j.jad.2023.01.085] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/05/2022] [Revised: 12/26/2022] [Accepted: 01/21/2023] [Indexed: 01/28/2023]
Abstract
OBJECTIVES Increasing depressive symptoms have become an urgent public health concern worldwide. This study aims to explore the correlation between personality traits and changes in depressive symptoms before and after the COVID-19 outbreak and to examine the gender difference in this association further. METHODS Data were obtained from the China Family Panel Studies (CFPS, wave in 2018 and 2020). A total of 16,369 residents aged 18 and above were included in this study. Multinomial logistic regression analysis was used to examine whether personality traits were associated with changes in depressive symptoms. We also analyzed whether there was an interaction effect of gender and personality traits on depressive symptoms. RESULTS Conscientiousness, extroversion, and agreeableness are negatively associated with depressive symptoms, while neuroticism and openness are positively related. Gender moderates the relationship between personality traits and depressive symptoms. Compared to men, women have demonstrated a stronger association between neuroticism (OR = 0.79; 95 % CI = 0.66, 0.94), conscientiousness (OR = 1.40; 95 % CI = 1.15, 1.69), and persistent depressive symptoms. LIMITATIONS Given its longitudinal study design, it is insufficient to draw a causal inference between personality traits and depressive symptoms. CONCLUSION Personality traits and their various dimensions are correlated with changes in depressive symptoms. Persistent depressive symptoms are positively related to neuroticism and negatively associated with conscientiousness. Women demonstrate a stronger association between personality traits and persistent depressive symptoms. Thus, in Chinese adults' mental health intervention and prevention programs, personality and gender-specific strategies should be considered, especially in the context of the COVID-19 pandemic.
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Affiliation(s)
- Ting Wang
- Department of Health Policy and Management, School of Public Health, Peking University, Beijing, China
| | - Qiaosheng Li
- Department of Health Policy and Management, School of Public Health, Peking University, Beijing, China
| | - Haoran Liu
- Department of Health Policy and Management, School of Public Health, Peking University, Beijing, China
| | - Qiaoxin Shi
- Department of Health Policy and Management, School of Public Health, Peking University, Beijing, China
| | - Fan Yang
- Department of Health Policy and Management, School of Public Health, Peking University, Beijing, China
| | - Bo Zhang
- Department of Neurology and ICCTR Biostatistics and Research Design Center, Boston Children's Hospital, Harvard Medical School, 02115 Boston, MA, USA
| | - Farooq Ahmed
- Department of Anthropology, Quaid-I-Azam University Islamabad, Islamabad, Pakistan
| | - Weiyan Jian
- Department of Health Policy and Management, School of Public Health, Peking University, Beijing, China.
| | - Jing Guo
- Department of Health Policy and Management, School of Public Health, Peking University, Beijing, China.
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Kučera D, Haviger J, Havigerová JM. Personality and Word Use: Study on Czech Language and the Big Five. JOURNAL OF PSYCHOLINGUISTIC RESEARCH 2022; 51:1165-1196. [PMID: 35579837 DOI: 10.1007/s10936-022-09892-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 05/02/2022] [Indexed: 06/15/2023]
Abstract
The study is a follow-up to three published anglophone researches examining the relation between the use of linguistic categories and personality characteristics as outlined in the Big Five model, with the purpose of replicating these and elaborating for the Czech language. The comparative research study in Czech focuses on analysis of both grammatical and semantic variables in six types of text (written and oral), produced by N = 200 participants. Within the study, there were six confirmed relations, however, these appear only in certain types of text. The results show not only an essential role of the text register, but they also allow us to evaluate the universality of findings of studies in English in comparison with other, especially Slavic, languages.
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Affiliation(s)
- Dalibor Kučera
- Department of Psychology, Faculty of Education, University of South Bohemia, Dukelská 245/9, 37001, České Budějovice, Czech Republic.
| | - Jiří Haviger
- Department of Informatics and Quantitative Methods, Faculty of Informatics and Management, University of Hradec Králové, Hradec Králové, Czech Republic
| | - Jana M Havigerová
- Institute of Psychology, Faculty of Arts, Masaryk University, Brno, Czech Republic
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Spitzley LA, Wang X, Chen X, Burgoon JK, Dunbar NE, Ge S. Linguistic measures of personality in group discussions. Front Psychol 2022; 13:887616. [PMID: 36186305 PMCID: PMC9523152 DOI: 10.3389/fpsyg.2022.887616] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Accepted: 08/15/2022] [Indexed: 11/26/2022] Open
Abstract
This investigation sought to find the relationships among multiple dimensions of personality and multiple features of language style. Unlike previous investigations, after controlling for such other moderators as culture and socio-demographics, the current investigation explored those dimensions of naturalistic spoken language that most closely align with communication. In groups of five to eight players, participants (N = 340) from eight international locales completed hour-long competitive games consisting of a series of ostensible missions. Composite measures of quantity, lexical diversity, sentiment, immediacy and negations were measured with an automated tool called SPLICE and with Linguistic Inquiry and Word Count. We also investigated style dynamics over the course of an interaction. We found predictors of extraversion, agreeableness, and neuroticism, but overall fewer significant associations than prior studies, suggesting greater heterogeneity in language style in contexts entailing interactivity, conversation rather than solitary message production, oral rather than written discourse, and groups rather than dyads. Extraverts were found to maintain greater linguistic style consistency over the course of an interaction. The discussion addresses the potential for Type I error when studying the relationship between language and personality.
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Affiliation(s)
- Lee A. Spitzley
- Department of Information Security and Digital Forensics, University at Albany, SUNY, Albany, NY, United States
- *Correspondence: Lee A. Spitzley,
| | - Xinran Wang
- Department of Management Information Systems, University of Arizona, Tucson, AZ, United States
- Center for the Management of Information Systems, University of Arizona, Tucson, AZ, United States
| | - Xunyu Chen
- Department of Management Information Systems, University of Arizona, Tucson, AZ, United States
- Center for the Management of Information Systems, University of Arizona, Tucson, AZ, United States
| | - Judee K. Burgoon
- Center for the Management of Information Systems, University of Arizona, Tucson, AZ, United States
| | - Norah E. Dunbar
- Department of Communication, University of California, Santa Barbara, Santa Barbara, CA, United States
| | - Saiying Ge
- Department of Management Information Systems, University of Arizona, Tucson, AZ, United States
- Center for the Management of Information Systems, University of Arizona, Tucson, AZ, United States
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Jackson A, Doidge C, Green M, Kaler J. Understanding public preferences for different dairy farming systems using a mixed-methods approach. J Dairy Sci 2022; 105:7492-7512. [DOI: 10.3168/jds.2022-21829] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2022] [Accepted: 05/19/2022] [Indexed: 11/19/2022]
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The dashang feature in social media: a personality and justice theory perspective. INFORMATION TECHNOLOGY & PEOPLE 2022. [DOI: 10.1108/itp-08-2018-0389] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
PurposeDashang refers to a reward given voluntarily to street performers in return for their performance. Some social media platforms have created a way to integrate this as a function, referred to as the dashang feature, to allow users to reward live performers online as well. Over the last few years, this function has become extremely popular among social media users, as it recreates the nostalgic experience of watching street performances. Platforms now consider it indispensable, as it has become a source of substantial revenue (commission on rewards earned by performers). However, not all users reward performers. For each user who pays, there are many more who lurk on the platform. This study examines the reasons for these differences using the Big Five personality perspective and justice theory.Design/methodology/approachWe develop an empirical model using the Big Five theory and justice theory and test it using empirical data collected through a survey of WeChat users.FindingsThe results indicate that distributive justice, interpersonal justice and informational justice are essential factors in relation to social media users' use of the dashang feature. It is also found that personality type affects these three factors.Originality/valueThis study makes three key contributions. First, it examines the factors that influence users' voluntary use of the dashang feature using the lenses of the Big Five theory and justice theory. Second, this study extends previous results on perceived justice to examine use of the dashang feature in social media. Third, this study applies these theories to the study of consumer behavior by exploring the role of user characteristics in social media use.
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Kučera D, Mehl MR. Beyond English: Considering Language and Culture in Psychological Text Analysis. Front Psychol 2022; 13:819543. [PMID: 35310262 PMCID: PMC8931497 DOI: 10.3389/fpsyg.2022.819543] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2021] [Accepted: 02/14/2022] [Indexed: 11/25/2022] Open
Abstract
The paper discusses the role of language and culture in the context of quantitative text analysis in psychological research. It reviews current automatic text analysis methods and approaches from the perspective of the unique challenges that can arise when going beyond the default English language. Special attention is paid to closed-vocabulary approaches and related methods (and Linguistic Inquiry and Word Count in particular), both from the perspective of cross-cultural research where the analytic process inherently consists of comparing phenomena across cultures and languages and the perspective of generalizability beyond the language and the cultural focus of the original investigation. We highlight the need for a more universal and flexible theoretical and methodological grounding of current research, which includes the linguistic, cultural, and situational specifics of communication, and we provide suggestions for procedures that can be implemented in future studies and facilitate psychological text analysis across languages and cultures.
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Affiliation(s)
- Dalibor Kučera
- Department of Psychology, Faculty of Education, University of South Bohemia in České Budějovice, České Budějovice, Czechia
| | - Matthias R. Mehl
- Department of Psychology, College of Science, University of Arizona, Tucson, AZ, United States
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