2023
DOI: 10.3389/fpsyg.2022.1066628
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China public emotion analysis under normalization of COVID-19 epidemic: Using Sina Weibo

Abstract: The prevention and control of the coronavirus disease 2019 (COVID-19) epidemic in China has entered a phase of normalization. The basis for evaluating and improving public health strategies is understanding the emotions and concerns of the public. This study establishes a fine-grained emotion-classification model to annotate the emotions of 32,698 Sina Weibo posts related to COVID-19 prevention and control from July 2022 to August 2022. The Dalian University of Technology (DLUT) emotion-classification system w… Show more

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Cited by 4 publications
(3 citation statements)
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“…Under the normalization of the COVID-19 epidemic, the topics changed to infection and death caused by the COVID-19 epidemic, control of personnel with positive nucleic acid tests, and persistence of the COVID-19 epidemic, etc. [ 30 ]. Therefore, at the different stages of the COVID-19 epidemic, the topics discussed by the internet-using public have been different.…”
Section: Discussionmentioning
confidence: 99%
“…Under the normalization of the COVID-19 epidemic, the topics changed to infection and death caused by the COVID-19 epidemic, control of personnel with positive nucleic acid tests, and persistence of the COVID-19 epidemic, etc. [ 30 ]. Therefore, at the different stages of the COVID-19 epidemic, the topics discussed by the internet-using public have been different.…”
Section: Discussionmentioning
confidence: 99%
“…A considerable amount of content was mentioned in theWeibo posts that was not related to the sentiment analysis and had to be cleaned. In this study, irrelevant content, such as Weibo topic, user name, and URL (Uniform Resource Locator) using regular expressions, was eliminated and then stop words removed using the Baidu stop words dictionary [ 12] . Organize the original data: delete website addresses with titles and links in the data; Delete the signature time in the data; Delete unintentional words such as "unfold", "capture", and "webpage link".…”
Section: Data Collectionmentioning
confidence: 99%
“…Perplexity is a common criterion for assessing the effectiveness of language models (Klakow and Peters, 2002). A lower perplexity indicates that the number of topics corresponding to this perplexity value is more reasonable , Zhang et al, 2022.…”
Section: Text Classi Cation Based On the Latent Dirichlet Allocation ...mentioning
confidence: 99%