Impact of COVID-19 Pandemic on Social Determinants of Health Issues of Marginalized Black and Asian Communities: A Social Media Analysis Empowered by Natural Language Processing.

Purpose: This study aims to understand the impact of the COVID-19 pandemic on social determinants of health (SDOH) of marginalized racial/ethnic US population groups, specifically African Americans and Asians, by leveraging natural language processing (NLP) and machine learning (ML) techniques on ra...

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Publicado en:Journal of Racial & Ethnic Health Disparities Vol. 12; no. 3; pp. 1641 - 1657
Autores principales: Whitfield, Christopher, Liu, Yang, Anwar, Mohd
Formato: pictorial research tables/charts Journal Article
Publicado: Springer Nature Jun2025
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Jun2025
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      pub: Springer Nature
      place: New York, New York
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        10.1007/s40615-024-01996-0
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        atl: Impact of COVID-19 Pandemic on Social Determinants of Health Issues of Marginalized Black and Asian Communities: A Social Media Analysis Empowered by Natural Language Processing.
      aug:
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          Whitfield, Christopher
          Liu, Yang
          Anwar, Mohd
        affil: https://ror.org/02aze4h65 North Carolina A&T State University, 27411, Greensboro, NC, USA
      sug:
        subj:
          COVID-19 Pandemic Adverse Effects
          Social Determinants of Health Ethical Issues
          Black Persons
          Asians
          Minority Groups United States
          Social Media
          Natural Language Processing Methods
          Outcome Assessment
          Human
          Male
          Female
          Adult
          United States
          Healthcare Disparities
          Machine Learning
          Research Methodology
          Racism
          Dissent and Disputes
          Social Control
          White Supremacy
          Discrimination
          Funding Source
          Adult: 19-44 years
          Male
          Female
      ab: Purpose: This study aims to understand the impact of the COVID-19 pandemic on social determinants of health (SDOH) of marginalized racial/ethnic US population groups, specifically African Americans and Asians, by leveraging natural language processing (NLP) and machine learning (ML) techniques on race-related spatiotemporal social media text data. Specifically, this study establishes the extent to which Latent Dirichlet Allocation (LDA) and Gibbs Sampling Dirichlet Multinomial Mixture (GSDMM)-based topic modeling determines social determinants of health (SDOH) categories, and how adequately custom named-entity recognition (NER) detects key SDOH factors from a race/ethnicity-related Reddit data corpus. Methods: In this study, we collected race/ethnicity-specific data from 5 location subreddits including New York City, NY; Los Angeles, CA; Chicago, IL; Philadelphia, PA; and Houston, TX from March to December 2019 (before COVID-19 pandemic) and from March to December 2020 (during COVID-19 pandemic). Next, we applied methods from natural language processing and machine learning to analyze SDOH issues from extracted Reddit comments and conversation threads using feature engineering, topic modeling, and custom named-entity recognition (NER). Results: Topic modeling identified 35 SDOH-related topics. The SDOH-based custom NER analyses revealed that the COVID-19 pandemic significantly impacted SDOH issues of marginalized Black and Asian communities. On average, the Social and Community Context (SCC) category of SDOH had the highest percent increase (366%) from the pre-pandemic period to the pandemic period across all locations and population groups. Some of the detected SCC issues were racism, protests, arrests, immigration, police brutality, hate crime, white supremacy, and discrimination. Conclusion: Reddit social media platform can be an alternative source to assess the SDOH issues of marginalized Black and Asian communities during the COVID-19 pandemic. By employing NLP/ML techniques such as LDA/GSDMM-based topic modeling and custom NER on a race/ethnicity-specific Reddit corpus, we uncovered various SDOH issues affecting marginalized Black and Asian communities that were significantly worsened during the COVID-19 pandemic. As a result of conducting this research, we recommend that researchers, healthcare providers, and governments utilize social media and collaboratively formulate responses and policies that will address SDOH issues during public health crises.
      pubtype: Academic Journal
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        research
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        Journal Article
      ougenre: Article
    language: English
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