Characterizing Public Sentiments and Drug Interactions in the COVID-19 Pandemic Using Social Media: Natural Language Processing and Network Analysis

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Pubblicato in:	Journal of Medical Internet Research vol. 27 (2025), p. e63755
Autore principale:	Li, Wanxin
Altri autori:	Hua, Yining, Zhou, Peilin, Zhou, Li, Xu, Xin, Yang, Jie
Pubblicazione:	Gunther Eysenbach MD MPH, Associate Professor
Soggetti:	Language Analysis COVID-19 vaccines Accuracy Datasets Application programming interface Public health Drug interactions Data mining Celebrities Social networks Data analysis Efficacy Acknowledgment Pharmacovigilance Physical symptoms Drug abuse Drug therapy Ivermectin Matrices Drugs Sentiment analysis Health surveillance Multimedia Misinformation Social media COVID-19 Pandemics Medical research Data collection Critical incidents Natural language processing Topics Network analysis Public opinion Vitamin D Comorbidity Public safety Normalization Medical treatment Vitamins Discourse analysis Computer mediated communication Mass media Mass media images Fame Epidemiology Recognition Attitudes Surveillance Drug effects Language modeling
Accesso online:	Citation/Abstract Full Text + Graphics Full Text - PDF
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