ArticleBiotech (Basel (Switzerland))2022
Investigating Topic Modeling Techniques to Extract Meaningful Insights in Italian Long COVID Narration.
Article in Biotech (Basel (Switzerland)), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Consistency in North Korean Medical Academic Research Topics During the COVID-19 Pandemic: A Text Mining Analysis.Journal of Korean medical science · 2026Article
- Immunological Mechanisms and Machine Learning Applications in Post-COVID-19 Syndrome: A Narrative Review.Microorganisms · 2026Article
- BERTopic-driven term extraction from biomedical texts toward ontology population: evaluating vaccine ontology with Plotkin's vaccines corpus.Journal of biomedical semantics · 2026Article
- Article
- Finding Long-COVID: Temporal Topic Modeling of Electronic Health Records from the N3C and RECOVER Programs.medRxiv : the preprint server for health sciences · 2024Article
- Machine Learning-based Analysis of Publications Funded by the National Institutes of Health's Initial COVID-19 Pandemic Response.Open forum infectious diseases · 2024Article
- Text mining of verbal autopsy narratives to extract mortality causes and most prevalent diseases using natural language processing.PloS one · 2024Article
- Examining the Public Messaging on 'Loneliness' over Social Media: An Unsupervised Machine Learning Analysis of Twitter Posts over the Past Decade.Healthcare (Basel, Switzerland) · 2023Article
- Obesity-Related Discourse on Facebook and Instagram Throughout the COVID-19 Pandemic: Comparative Longitudinal Evaluation.JMIR infodemiology · 2023Article
- Did the public attribute the Flint Water Crisis to racism as it was happening? Text analysis of Twitter data to examine causal attributions to racism during a public health crisis.Journal of computational social science · 2023Article
- A survey on the role of artificial intelligence in managing Long COVID.Frontiers in artificial intelligence · 2023Review
- Bioinformatics and High-Performance Computing Methods for Deciphering and Fighting COVID-19-Editorial.Biotech (Basel (Switzerland)) · 2022Article
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Authors and funding
5 authors.
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Abstract
Through an adequate survey of the history of the disease, Narrative Medicine (NM) aims to allow the definition and implementation of an effective, appropriate, and shared treatment path. In the present study different topic modeling techniques are compared, as Latent Dirichlet Allocation (LDA) and topic modeling based on BERT transformer, to extract meaningful insights in the Italian narration of COVID-19 pandemic. In particular, the main focus was the characterization of Post-acute Sequelae of COVID-19, (i.e., PASC) writings as opposed to writings by health professionals and general reflections on COVID-19, (i.e., non-PASC) writings, modeled as a semi-supervised task. The results show that the BERTopic-based approach outperforms the LDA-base approach by grouping in the same cluster the 97.26% of analyzed documents, and reaching an overall accuracy of 91.97%.
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