Impact of information timeliness and richness on public engagement on social media during COVID-19 pandemic: An empirical investigation based on NLP and machine learning

This paper investigates how information timeliness and richness affect public engagement using text data from China's largest social media platform during times of the COVID-19 pandemic. We utilize a similarity calculation method based on natural language processing (NLP) and text mining to eva...

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Detalles Bibliográficos
Autores principales: Li, Kai, Zhou, Cheng, Luo, Xin (Robert), Benitez, Jose, Liao, Qinyu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier B.V. 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8839801/
https://www.ncbi.nlm.nih.gov/pubmed/35185227
http://dx.doi.org/10.1016/j.dss.2022.113752

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8839801/
https://www.ncbi.nlm.nih.gov/pubmed/35185227
http://dx.doi.org/10.1016/j.dss.2022.113752

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