Sentiment Analysis on Chinese Weibo Regarding COVID-19

Lyu, Xiaoting; Chen, Zhe; Wu, Di; Wang, Wei

doi:10.1007/978-3-030-60450-9_56

Cited by 22 publications

(17 citation statements)

References 8 publications

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“…The changing trend of public sentiment with time in the epidemic shows the characteristics of violent fluctuations in the early stage, stability in the middle stage, and rise in the late stage. The results are mutually verified with some existing research conclusions [36,37]. In the early stages of an outbreak, public sentiment tends to be volatile for two reasons: first, various problems are exposed in the early stage of the epidemic, although…”

Section: Significance Of Resultssupporting

confidence: 83%

The Impact of Shanghai Epidemic, China, 2022 on Public Psychology: A Sentiment Analysis of Microblog Users by Data Mining

Wang

Qin

2022

Sustainability

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The Shanghai epidemic (COVID-19) is another large-scale epidemic in China’s central cities in the post-epidemic era from the end of March 2022. It is of great significance to study the public’s attitude towards the Shanghai epidemic to support healthy psychology and a positive attitude. This study used crawler technology to obtain the Weibo data related to the epidemic situation in Shanghai that was published by users. The crawled microblogs were preprocessed, and the BosonNLP sentiment dictionary for attitude classification was selected. The Chinese vocabulary ontology for 21 emotion classifications was also used. The results showed that the general attitude of the public in Shanghai was positive. This fluctuated greatly in the initial stage and gradually increased in the later stage. Through text mining, it is clear that goods and materials, nucleic acid virus testing, and other aspects of the epidemic in Shanghai are concerning for the public. The public attitude in areas that are close to the epidemic center is relatively more negative. The study can provide references for policymakers to fight COVID-19 by improving public attitude and solving urgent matters.

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Section: Significance Of Resultssupporting

confidence: 83%

The Impact of Shanghai Epidemic, China, 2022 on Public Psychology: A Sentiment Analysis of Microblog Users by Data Mining

Wang

Qin

2022

Sustainability

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“…Since February 2020, public attention to COVID-19 has declined on Sina Weibo , a Chinese microblog platform, and people's positive feelings have significantly increased. The main reason for this phenomenon is the successful prevention and control of the pandemic in China in the first wave of the outbreak ( Lyu, Chen, & Wu et al, 2020 ; Zhao, Cheng, & Yu et al, 2020 ; Cui & Kertész, 2021 ).…”

Section: Literature Reviewmentioning

confidence: 99%

Study on the mechanism of public attention to a major event: The outbreak of COVID-19 in China

Liu

2022

Sustainable Cities and Society

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“…Setup. To ensure a fair comparison, we select a newly developed dataset on COVID-19, collected also from Weibo using hashtags related to COVID-19 by Lyu et al (2020). The dataset contains 21,174 posts with fine-grained emotion annotations.…”

Section: Differences Between Complaints and Sentimentmentioning

confidence: 99%

Analyzing the Intensity of Complaints on Social Media

Fang¹,

Zong²,

Li³

et al. 2022

Preprint

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Complaining is a speech act that expresses a negative inconsistency between reality and human expectations. While prior studies mostly focus on identifying the existence or the type of complaints, in this work, we present the first study in computational linguistics of measuring the intensity of complaints from text. Analyzing complaints from such perspective is particularly useful, as complaints of certain degrees may cause severe consequences for companies or organizations. We create the first Chinese dataset containing 3,103 posts about complaints from Weibo, a popular Chinese social media platform. These posts are then annotated with complaints intensity scores using Best-Worst Scaling (BWS) method. We show that complaints intensity can be accurately estimated by computational models with the best mean square error achieving 0.11. Furthermore, we conduct a comprehensive linguistic analysis around complaints, including the connections between complaints and sentiment, and a cross-lingual comparison for complaints expressions used by Chinese and English speakers. We finally show that our complaints intensity scores can be incorporated for better estimating the popularity of posts on social media. 1

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Sentiment Analysis on Chinese Weibo Regarding COVID-19

Cited by 22 publications

References 8 publications

The Impact of Shanghai Epidemic, China, 2022 on Public Psychology: A Sentiment Analysis of Microblog Users by Data Mining

The Impact of Shanghai Epidemic, China, 2022 on Public Psychology: A Sentiment Analysis of Microblog Users by Data Mining

Study on the mechanism of public attention to a major event: The outbreak of COVID-19 in China

Analyzing the Intensity of Complaints on Social Media

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