Research on the evolution of cross-platform online public opinion for public health emergencies considering stakeholders.
Journal
PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081
Informations de publication
Date de publication:
2024
2024
Historique:
received:
18
12
2023
accepted:
21
05
2024
medline:
25
6
2024
pubmed:
25
6
2024
entrez:
25
6
2024
Statut:
epublish
Résumé
To explore the different processes of the themes and emotional evolution of various stakeholders in the network public opinion of sudden public health emergencies at different stages of the public opinion evolution lifecycle. This paper proposes a cross-platform analysis method for online public opinion during the public health emergencies based on stakeholders. Firstly, data from multiple platforms are collected and integrated. Secondly, stakeholders are categorized and the stages of public opinion evolution are determined based on stakeholder theory and lifecycle theory. Finally, the Latent Dirichlet Allocation (LDA)+Word2vec model and Convolutional Neural Network (CNN) model are used to analyze the themes and emotional evolution of stakeholders during different stages of public opinion evolution. There are differences in the evolution patterns of different types of stakeholders. The evolution process of stakeholders' focus points exhibits a two-stage transition from concentration to divergence. The focus points of stakeholders are closely associated with their respective social domains. The emotions of the public undergo a three-stage process of positive-negative-positive change. This study can provide a reference for the government to have a more comprehensive understanding of the development trend of public opinion and reduce the negative impact of public opinion.
Identifiants
pubmed: 38917155
doi: 10.1371/journal.pone.0304877
pii: PONE-D-23-42634
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
e0304877Informations de copyright
Copyright: © 2024 Shen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Déclaration de conflit d'intérêts
The authors have declared that no competing interests exist.