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Applying machine-learning to rapidly analyze large qualitative text datasets to inform the COVID-19 pandemic response: comparing human and machine-assisted topic analysis techniques.
Towler, Lauren; Bondaronek, Paulina; Papakonstantinou, Trisevgeni; Amlôt, Richard; Chadborn, Tim; Ainsworth, Ben; Yardley, Lucy.
Affiliation
  • Towler L; School of Psychology, University of Southampton, Southampton, United Kingdom.
  • Bondaronek P; School of Psychological Science, University of Bristol, Bristol, United Kingdom.
  • Papakonstantinou T; Department of Health and Social Care, Office for Health Improvement and Disparities, London, United Kingdom.
  • Amlôt R; Institute for Health Informatics, University College London, London, United Kingdom.
  • Chadborn T; Department of Health and Social Care, Office for Health Improvement and Disparities, London, United Kingdom.
  • Ainsworth B; Department of Experimental Psychology, Division of Psychology and Language Sciences, University College London, London, United Kingdom.
  • Yardley L; Behavioural Science and Insights Unit, UK Health Security Agency, London, United Kingdom.
Front Public Health ; 11: 1268223, 2023.
Article in En | MEDLINE | ID: mdl-38026376
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: COVID-19 Limits: Humans Language: En Journal: Front Public Health Year: 2023 Document type: Article Affiliation country: Reino Unido Country of publication: Suiza
Fulltext
Add to My VHL
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PubMed Links
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: COVID-19 Limits: Humans Language: En Journal: Front Public Health Year: 2023 Document type: Article Affiliation country: Reino Unido Country of publication: Suiza