Communicating Concerns, Emotional Expressions, and Disparities on Ethnic Communities on Social Media during the COVID-19 Pandemic: A Structural Topic Modeling Approach

Research output: Contribution to journalJournal articleResearchpeer-review

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Communicating Concerns, Emotional Expressions, and Disparities on Ethnic Communities on Social Media during the COVID-19 Pandemic : A Structural Topic Modeling Approach. / Lu, Jiahui; Liu, Jun.

In: American Behavioral Scientist, 2023.

Research output: Contribution to journalJournal articleResearchpeer-review

Harvard

Lu, J & Liu, J 2023, 'Communicating Concerns, Emotional Expressions, and Disparities on Ethnic Communities on Social Media during the COVID-19 Pandemic: A Structural Topic Modeling Approach', American Behavioral Scientist. https://doi.org/10.1177/00027642231164046

APA

Lu, J., & Liu, J. (2023). Communicating Concerns, Emotional Expressions, and Disparities on Ethnic Communities on Social Media during the COVID-19 Pandemic: A Structural Topic Modeling Approach. American Behavioral Scientist. https://doi.org/10.1177/00027642231164046

Vancouver

Lu J, Liu J. Communicating Concerns, Emotional Expressions, and Disparities on Ethnic Communities on Social Media during the COVID-19 Pandemic: A Structural Topic Modeling Approach. American Behavioral Scientist. 2023. https://doi.org/10.1177/00027642231164046

Author

Lu, Jiahui ; Liu, Jun. / Communicating Concerns, Emotional Expressions, and Disparities on Ethnic Communities on Social Media during the COVID-19 Pandemic : A Structural Topic Modeling Approach. In: American Behavioral Scientist. 2023.

Bibtex

@article{7083d05b1bd4484bbeb2e5f645bc7316,
title = "Communicating Concerns, Emotional Expressions, and Disparities on Ethnic Communities on Social Media during the COVID-19 Pandemic: A Structural Topic Modeling Approach",
abstract = "Ethnic and racial disparities in the current coronavirus (COVID-19) pandemic raise significant concerns. This study analyzes social media discourses toward four ethnic communities in the US during the pandemic and reveals disparities in pandemic experiences among them. A total of 488,029 tweets mentioning one of four ethnic communities, i.e. Asians, Blacks, Hispanics, and Native Americans, were investigated by a structural topic modeling approach with emotional expressions and time as covariates in the topic model. The results demonstrate that discourses about Asian, Hispanics, and Native American communities were often induced by pandemic-related events, concerning topics beyond one{\textquoteright}s community, and reflecting an experience of implicit racism and an adoption of technical supports from health systems. Meanwhile, discourses about Blacks were racially-related, discussing topics within the community, and reflecting an experience of explicit racism and an adoption of psychological supports from ingroup. We discuss the implications of our findings on ethnic health disparities.",
author = "Jiahui Lu and Jun Liu",
year = "2023",
doi = "https://doi.org/10.1177/00027642231164046",
language = "English",
journal = "American Behavioral Scientist",
issn = "0002-7642",
publisher = "SAGE Publications",

}

RIS

TY - JOUR

T1 - Communicating Concerns, Emotional Expressions, and Disparities on Ethnic Communities on Social Media during the COVID-19 Pandemic

T2 - A Structural Topic Modeling Approach

AU - Lu, Jiahui

AU - Liu, Jun

PY - 2023

Y1 - 2023

N2 - Ethnic and racial disparities in the current coronavirus (COVID-19) pandemic raise significant concerns. This study analyzes social media discourses toward four ethnic communities in the US during the pandemic and reveals disparities in pandemic experiences among them. A total of 488,029 tweets mentioning one of four ethnic communities, i.e. Asians, Blacks, Hispanics, and Native Americans, were investigated by a structural topic modeling approach with emotional expressions and time as covariates in the topic model. The results demonstrate that discourses about Asian, Hispanics, and Native American communities were often induced by pandemic-related events, concerning topics beyond one’s community, and reflecting an experience of implicit racism and an adoption of technical supports from health systems. Meanwhile, discourses about Blacks were racially-related, discussing topics within the community, and reflecting an experience of explicit racism and an adoption of psychological supports from ingroup. We discuss the implications of our findings on ethnic health disparities.

AB - Ethnic and racial disparities in the current coronavirus (COVID-19) pandemic raise significant concerns. This study analyzes social media discourses toward four ethnic communities in the US during the pandemic and reveals disparities in pandemic experiences among them. A total of 488,029 tweets mentioning one of four ethnic communities, i.e. Asians, Blacks, Hispanics, and Native Americans, were investigated by a structural topic modeling approach with emotional expressions and time as covariates in the topic model. The results demonstrate that discourses about Asian, Hispanics, and Native American communities were often induced by pandemic-related events, concerning topics beyond one’s community, and reflecting an experience of implicit racism and an adoption of technical supports from health systems. Meanwhile, discourses about Blacks were racially-related, discussing topics within the community, and reflecting an experience of explicit racism and an adoption of psychological supports from ingroup. We discuss the implications of our findings on ethnic health disparities.

U2 - https://doi.org/10.1177/00027642231164046

DO - https://doi.org/10.1177/00027642231164046

M3 - Journal article

JO - American Behavioral Scientist

JF - American Behavioral Scientist

SN - 0002-7642

ER -

ID: 337248786