ArticleProceedings of the National Academy of Sciences of the United States of America2022
Integrating topic modeling and word embedding to characterize violent deaths.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- A topic modeling analysis of stigma dimensions, social, and related behavioral circumstances in clinical notes among patients with HIV.International journal of medical informatics · 2026Article
- Theoretical foundations and limits of word embeddings: What types of meaning can they capture?Sociological methods & research · 2024Article
- Talk of Family: How Institutional Overlap Shapes Family-Related Discourse Across Social Class.The Russell Sage Foundation journal of the social sciences : RSF · 2024Article
- Limitations of Sexual Orientation and Gender Identity Information as Reported in the National Violent Death Reporting System.LGBT health · 2024Article
- Gendered Patterns in Manifest and Latent Mental Health Indicators Among Suicide Decedents: 2003-2020 National Violent Death Reporting System (NVDRS).American journal of public health · 2024Article
- New Research Efforts and Approaches Are Needed to Change the Current Youth Suicide Risk Trends Among Health Disparity Groups.American journal of public health · 2024Article
- Identifying Witnessed Suicides in National Violent Death Reporting System Narratives.Healthcare (Basel, Switzerland) · 2024Article
- Policy instruments facilitate China's COVID-19 work resumption.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Research utility and limitations of textual data in the National Violent Death Reporting System: a scoping review and recommendations.Injury epidemiology · 2023Article
- Examining Intimate Partner Violence-Related Fatalities: Past Lessons and Future Directions Using U.S. National Data.Journal of family violence · 2023Article
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Authors and funding
5 authors.
Funding
Abstract
SignificanceWe introduce an approach to identify latent topics in large-scale text data. Our approach integrates two prominent methods of computational text analysis: topic modeling and word embedding. We apply our approach to written narratives of violent death (e.g., suicides and homicides) in the National Violent Death Reporting System (NVDRS). Many of our topics reveal aspects of violent death not captured in existing classification schemes. We also extract gender bias in the topics themselves (e.g., a topic about long guns is particularly masculine). Our findings suggest new lines of research that could contribute to reducing suicides or homicides. Our methods are broadly applicable to text data and can unlock similar information in other administrative databases.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.