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

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Opis bibliograficzny
Wydane w:	Journal of Medical Internet Research vol. 27 (2025), p. e63755
1. autor:	Li, Wanxin
Kolejni autorzy:	Hua, Yining, Zhou, Peilin, Zhou, Li, Xu, Xin, Yang, Jie
Wydane:	Gunther Eysenbach MD MPH, Associate Professor
Hasła przedmiotowe:	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
Dostęp online:	Citation/Abstract Full Text + Graphics Full Text - PDF
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