Leveraging natural language processing (NLP) to understand media framing of Lyme disease.

Research demonstrates that media frame our understanding of health-related issues. This study leverages Natural Language Processing (NLP) to explore how media in five nations (Canada, Australia, New Zealand, England, and the United States) frame Lyme disease. The results showed that the Canadian Bro...

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Publicado en:Atlantic Journal of Communication Vol. 34; no. 1; pp. 79 - 94
Autores principales: Jia, Lili, Croucher, Stephen M., Gilbert, Leona
Formato: Artículo
Publicado: Taylor & Francis Ltd Jan-Mar2026
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Leveraging natural language processing (NLP) to understand media framing of Lyme disease.
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          Jia, Lili
          Croucher, Stephen M.
          Gilbert, Leona
        affil:
          Business Analytics, Massey University, Auckland, New Zealand
          Department of Communication, Strode Tower, Clemson University, Clemson, South Carolina
          Te?ted Oy, Jyväskylä, Finland
      su:
        Lyme disease
        Natural language processing
        Frames (Social sciences)
        Canadian Broadcasting Corp.
        Sentiment analysis
        United States
        Canada
      sug:
        subj:
          United States
          Canada
          Lyme disease
          Natural language processing
          Frames (Social sciences)
          Canadian Broadcasting Corp.
          Sentiment analysis
      ab: Research demonstrates that media frame our understanding of health-related issues. This study leverages Natural Language Processing (NLP) to explore how media in five nations (Canada, Australia, New Zealand, England, and the United States) frame Lyme disease. The results showed that the Canadian Broadcasting Corporation had the most media coverage of Lyme disease. Second, sentiment analysis demonstrated differences in overall sentiment among the outlets. VADER identified a balance between neutral sentiment in article titles and positivity in article content, while BERT revealed high negativity in titles and content. Third, key frames varied across the media, demonstrating the differing focus of each outlet.
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