Relay activism and the flows of contentious publicness on WeChat: a case study of COVID-19 in China

This paper explores a case of public contention against the censoring of a feature article about a COVID-19 whistleblower on the Chinese social media, WeChat. Moving beyond the normative theory of the public sphere and publics, we draw on Kavada and Poell's theory of 'contentious publicness' which is flexible enough to capture the complexity, diversity and hybridity of digital contention in the context of China. Through a combination of textual analysis and participatory observation, this article analyses how citizens challenged the censorship system and attempted to keep Dr Fen's story online through what we call 'relay activism'. Informed by the three dimensions of 'contentious publicness', we analyse the materiality of the communication infrastructure of WeChat and the temporal and spatial relations of the public contention (focusing primarily on WeChat and GitHub). In doing this, the paper contributes a more comprehensive approach to examining the social, structural and participatory characteristics of the contestation of censorship in China.

How Do Multiple Actors Conduct Science Communication About Omicron on Weibo: A Mixed‐Method Study

This article explores science communication about Omicron on Weibo by eight actors from November 2021 to June 2022. Regarding the themes of vaccines, symptoms, and medicines, we examined the actors' communication with content analysis, presented the interactions of different actors using social network analysis, and assessed the impact of weibos on public sentiment using SnowNLP and descriptive statistics. The results showed that scientists are still the most important actors, focusing on science issues and using contrasting and contextual frames. Central‐level media play an essential mediating role, relaying scientific knowledge. Science communication on Weibo had a positive impact on public sentiment. © 2023 by the author(s);licensee Cogitatio Press (Lisbon, Portugal). This article is licensed under a Creative Commons Attribution 4.0 International License (CC BY).

Public Opinion Analysis for the Covid-19 Pandemic Based on Sina Weibo Data

The outbreak of Covid-19 has been continuously affecting human lives and communities around the world in many ways. In order to effectively prevent and control the Covid-19 pandemic, public opinion is analyzed based on Sina Weibo data in this paper. Firstly the Weibo data was crawled from Sina website to be the experimental dataset. After preprocessing operations of data cleaning, word segmentation and stop words removal, Term Frequency Inverse Document Frequency (TF-IDF) method was used to perform feature extraction and vectorization. Then public opinion for the Covid-19 pandemic was analyzed, which included word cloud analysis based on text visualization, topic mining based on Latent Dirichlet Allocation (LDA) and sentiment analysis based on Naïve Bayes. The experimental results show that public opinion analysis based on Sina Weibo data can provide effective data support for prevention and control of the Covid-19 pandemic. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

The softening of Chinese digital propaganda: Evidence from the People's Daily Weibo account during the pandemic.

Introduction: Social media infuses modern relationships with vitality and brings a series of information dissemination with subjective consciousness. Studies have indicated that official Chinese media channels are transforming their communication style from didactic hard persuasion to softened emotional management in the digital era. However, previous studies have rarely provided valid empirical evidence for the communicational transformation. The study fills the gap by providing a longitudinal time-series analysis to reveal the pattern of communication of Chinese digital Chinese official media from 2019 to 2022. Method: The study crawler collected 43,259 posts from the People's Daily's Weibo account from 2019 to 2021. The study analyzed the textual data with using trained artificial intelligence models. Results: This study explored the practices of the People's Daily's Weibo account from 2019 to 2021, COVID-19 is hardly normalized as it is still used as the justification for extraordinary measures in China. This study confirmed that People's Daily's Weibo account posts are undergoing softenization transformation, with the use of soft news, positive energy promotion, and the embedding of sentiment. Although the outburst of COVID-19 temporarily increased the media's use of hard news, it only occur at the initial stage of the pandemic. Emotional posts occupy a nonnegligible amount of the People's Daily Weibo content. However, the majority of posts are emotionally neutral and contribute to shaping the authoritative image of the party press. Discussion: Overall, the People's Daily has softened their communication style on digital platforms and used emotional mobilization, distraction, and timely information provision to balance the political logic of building an authoritative media agency and the media logic of constructing audience relevance.

Weibo users and Academia's foci on tourism safety: Implications from institutional differences and digital divide.

Tourism safety is essential for tourists and tourism practitioners. This study conducted a bibliometric analysis using VOSviewer and CiteSpace for 2018 articles indexed on the Web of Science (WoS). It also analysed 7293 Weibo posts between 1977 and 2022 using Python, MYSQL, AI sentiment, and Tableau. The first tourism safety publication on WoS appeared in 1977, while the first Weibo microblog dated was dated back to 2011. Compared to the information posted on Weibo, the annual publications about tourism safety on WoS recorded a stable increment. On Web of Science (WoS), the academic staff and universities produced the largest number of tourism safety posts. On the flip side, the most productive organisations on Weibo are government agencies in popular tourism destinations. "Accident", "medical tourism", "environment", "mediating role", and "hospitality" were important burst nodes in tourism safety on WoS. "Quality", "accident", and health-related words were the foci on both Weibo and WoS. On Web of Science, the top 10 most popular keywords of tourism safety-related articles could be classified into two groups: health ("Covid-19", "restoration", "pandemics", "Sars-Cov-2", "Sars", "mental health") and IT terminologies ("big data", "artificial intelligence"). It has been concluded that "artificial intelligence (AI)" is more likely to be included in the keywords on tourism researched by academia. In contrast, the public may not know about or use AI in the tourism industry. Besides, the top 10 most popular keywords on Weibo related to tourism risks and hazards were drowning and traffic risks and hazards, such as drowning and traffic risks. The digital divide may explain such a difference: the academic circle benefits more from the digital age than laypersons. It may also be the result of institutional differences and information asymmetry.

How health organizations communicate about COVID-19 on social media: a comparative content analysis.

BACKGROUND: This study examined how different health organizations (i.e., the Chinese CDC, the Korean CDC, the United States CDC, and WHO) communicated about the COVID-19 pandemic on social media, thus providing implications for organizations touse social media effectively in global health crises in the future. METHODS: Three bilingual researchers conducted a content analysis ofsocial media posts (N = 1,343) of these health organizations on Twitter and Sina Weibo to explore the frames of the COVID-19 pandemic, the purposes, and the strategies to communicate about it. RESULTS: Prevention was the dominant frame of the social media content of these four health organizations. Information update was the major communication purpose for WHO, the United States CDC, and the Korean CDC; however, guidance was the primary communication purpose for the Chinese CDC. The United States CDC, the Chinese CDC, and the Korean CDC heavily relied on multiple social media strategies (i.e., visual, hyperlink, and authority quotation) in their communication to the public about the COVID-19 pandemic, whereas WHO primarily employed quoting authorities. Significantdifferences were revealed across these health organizations in frames, communication purposes, and strategies. Theoretical and practical implications and limitations were discussed. CONCLUSIONS: This study examined how different global health organizations communicate about the COVID-19 pandemic on social media. We discussed how and why these global health organizations communicate the COVID-19 pandemic, which would help health-related organizations design messages strategically on global public health issues in the future.

China public emotion analysis under normalization of COVID-19 epidemic: Using Sina Weibo.

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 was adjusted to form four pairs (eight categories) of bidirectional emotions: good-disgust, joy-sadness, anger-fear, and surprise-anticipation. A lexicon-based method was proposed to classify the emotions of Weibo posts. Based on the selected Weibo posts, the present study analyzed the Chinese public's sentiments and emotions. The results showed that positive sentiment accounted for 51%, negative sentiment accounted for 24%, and neutral sentiment accounted for 25%. Positive sentiments were dominated by good and joy emotions, and negative sentiments were dominated by fear and disgust emotions. The proportion of positive sentiments on official Weibo (accounts belonging to government departments and official media) is significantly higher than that on personal Weibo. Official Weibo users displayed a weak guiding effect on personal users in terms of positive sentiment and the two groups of users were almost completely synchronized in terms of negative sentiment. The linear discriminant analysis (LDA) was performed on the two negative emotions of fear and disgust in the personal posts. The present study found that the emotion of fear was mainly related to COVID-19 infection and death, control of people with positive nucleic acid tests, and the outbreak of local epidemic, while the emotion of disgust was mainly related to the long-term existence of the epidemic, the cost of nucleic acid tests, non-implementation of prevention and control measures, and the occurrence of foreign epidemics. These findings suggest that Chinese attitudes toward epidemic prevention and control are positive and optimistic; however, there is also a notable proportion of fear and disgust. It is expected that this study will help public health administrators to evaluate the effectiveness of possible countermeasures and work toward precise prevention and control of the COVID-19 epidemic.

Research on COVID-19 network public opinion events based on topic model and community detection algorithm

COVID-19 has caused a large number of online public opinion incidents. How to timely and effectively guide the resulting network public opinion has become an urgent problem to be solved. This paper collects more than 130,000 original Weibo posts during the Wuhan "city closure” incident, and analyses the topic characteristics of the incident on the basis of user classification through topic models and community detection algorithms. It was found that during this period, the government responded quickly to the epidemic and gained public support. For different Weibo users, officially certified users mainly publish information about the epidemic and epidemic prevention measures. Personally certified users mainly forwarded and transmitted official information actively, and they also expressed their opinions and made suggestions. Non-certified users actively expressed their emotions and opinions, so they were important users that reflect public opinion. © 2022 SPIE.

SARS-CoV-2 outbreak uplifted collectivistic expression in the Hubei Daily

Following the outbreak of SARS-CoV-2, collectivistic words have been used more frequently on Sina Weibo and the People's Daily. However, the studies on Sina Weibo and the People's Daily can only reflect the overall impact by SARS-CoV-2 in China. To examine the influence of SARS-CoV-2 on collectivism/individualism, we first investigated the Hubei Daily, an authoritative local media in Hubei, the first province to discover SARS-CoV-2, to see the impact of SARS-CoV-2 on collectivism/individualism. We analyzed data from the Hubei Daily, using the same collectivistic/individualistic words identified in prior studies and found that the outbreak of SARS-CoV-2 increased collectivism and decreased individualism significantly. Next, we analyzed the same data using the individualistic/collectivistic word bank created in a different cross-culture study based on Sina Weibo posts. The results showed that, during the SARS-CoV-2, collectivistic words were used more frequently;no significant changes were seen regarding individualist words. Lastly, we created a COVID-19 word bank and conducted a regression analysis to examine the relationship between collectivistic word frequency and COVID-19 word frequency in the after-breakout period of SARS-CoV-2 and found that the severity of SARS-CoV-2 predicted collectivist word frequency change in the Hubei Daily. © 2022 IEEE.

Consideration of the Effects of Covid-19 Delay in Psycholinguistic Research Lahore and Karachi at Facebook and Weibo

Numerous nations are taking severe isolate strategies to forestall the fast spread of COVID-19 (Covid Disease 2019) around the globe, for example, city lockdown. Urban areas in China and Italy were secured down in the beginning phase of the pandemic. The current investigation expects to analyze and analyze the effect of COVID-19 lockdown on people's mental states in China and Pakistan. We also carried out a survey (a) of Weibo customers and Twitter customers (geo-area = Karachi, Pakistan);(2) to have the customer's distributed posts filled in a span of fourteen days, then after locking down in each location (e.g. the lock-down date for Karachi, Pakistan, was 23 January 2020);Our current research was conducted at Jinnah Hospital, Lahore from March 2020 to September 2020. Results demonstrated that people zeroed in additional on "home", furthermore, communicated a more elevated level of psychological cycle after a lockdown in both Lahore and Karachi. Then, the degree of stress diminished, and the consideration regarding relaxation expanded in Karachi after the lockdown. The regard for gathering, religion, and feelings turned out to be more common in Lahore after the lockdown. Discoveries give leaders ideal proof on open responses and the effects on mental states in the COVID-19 setting, and have suggestions for proof based mental wellbeing mediations in two nations. Copyright © 2022, Anka Publishers. All rights reserved.

An Epistemic Trend or a Digital Pitfall? De-Westernizing Media and Communication Studies in Digital China

Governments hiding facts and truth from the public seems to have become a common phenomenon, especially during the social crisis in China. The practice of the public using various media to express dissent and opinions, to overcome government censorship, appears to contribute to freedom of speech. Inspired by widespread online articles during the COVID-19 pandemic in 2020, this paper argues that the flaws in this logic are the dualism, which digital media created (pro-democracy vs authoritarian;freedom vs control), in understanding media in China. By borrowing the discussion of the de-westernization of media and communication studies, the paper argues that the introduc-tion of digital media makes de-westernized studies in China harder because it prompts us to think "digitally."

Topic modeling and sentiment analysis of Chinese people's attitudes toward volunteerism amid the COVID-19 pandemic.

The COVID-19 pandemic has created an urgent need for volunteers to complement overwhelmed public health systems. This study aims to explore Chinese people's attitudes toward volunteerism amid the COVID-19 pandemic. To this end, we identify the latent topics in volunteerism-related microblogs on Weibo, the Chinese equivalent of Twitter using the topic modeling analysis via Latent Dirichlet Allocation (LDA). To further investigate the public sentiment toward the topics generated by LDA, we also conducted sentiment analysis on the sample posts using the open-source natural language processing (NLP) technique from Baidu. Through an in-depth analysis of 91,933 Weibo posts, this study captures 10 topics that are, in turn, distributed into five factors associated with volunteerism in China as motive fulfillment (n = 31,661, 34.44%), fear of COVID-19 (n = 22,597, 24.58%), individual characteristic (n = 17,688, 19.24%), government support (n = 15,482, 16.84%), and community effect (n = 4,505, 4.90%). The results show that motive fulfillment, government support, and community effect are the factors that could enhance positive attitudes toward volunteerism since the topics related to these factors report high proportions of positive emotion. Fear of COVID-19 and individual characteristic are the factors inducing negative sentiment toward volunteerism as the topics related to these factors show relatively high proportions of negative emotion. The provision of tailored strategies based on the factors could potentially enhance Chinese people's willingness to participate in volunteer activities during the COVID-19 pandemic.

Exploring public attitudes toward live-streaming fitness in China: A sentiment and content analysis of China's social media Weibo.

Objectives: Live-streaming fitness is perceived by the Chinese government as an invaluable means to reduce the prevalence of physical inactivity amid the COVID-19 pandemic. This study aims to investigate the public altitudes of the Chinese people toward live-streaming fitness and provide future health communication strategies on the public promotion of live-streaming fitness accordingly. Methods: This study collected live-streaming fitness-related microblog posts from July 2021 to June 2022 in Weibo, the Chinese equivalent to Twitter. We used the BiLSTM-CNN model to carry out the sentiment analysis, and the structured topic modeling (STM) method to conduct content analysis. Results: This study extracted 114,397 live-streaming fitness-related Weibo posts. Over 80% of the Weibo posts were positive during the period of the study, and over 85% were positive in half of the period. This study finds 8 topics through content analysis, which are fitness during quarantine; cost reduction; online community; celebrity effect; Industry; fitness injuries; live commerce and Zero Covid strategy. Conclusions: It is discovered that the public attitudes toward live-streaming fitness were largely positive. Topics related to celebrity effect (5-11%), fitness injuries (8-16%), live commerce (5-9%) and Zero Covid strategy (16-26%) showed upward trends in negative views of the Chinese people. Specific health communication strategy suggestions are given to target each of the negative topics.

(Mis)Information on Digital Platforms: Quantitative and Qualitative Analysis of Content From Twitter and Sina Weibo in the COVID-19 Pandemic.

Background: Misinformation about COVID-19 on social media has presented challenges to public health authorities during the pandemic. This paper leverages qualitative and quantitative content analysis on cross-platform, cross-national discourse and misinformation in the context of COVID-19. Specifically, we investigated COVID-19-related content on Twitter and Sina Weibo-the largest microblogging sites in the United States and China, respectively. Objective: Using data from 2 prominent microblogging platform, Twitter, based in the United States, and Sina Weibo, based in China, we compared the content and relative prevalence of misinformation to better understand public discourse of public health issues across social media and cultural contexts. Methods: A total of 3,579,575 posts were scraped from both Sina Weibo and Twitter, focusing on content from January 30, 2020, within 24 hours of when WHO declared COVID-19 a "public health emergency of international concern," and a week later, on February 6, 2020. We examined how the use and engagement measured by keyword frequencies and hashtags differ across the 2 platforms. A 1% random sample of tweets that contained both the English keywords "coronavirus" and "covid-19" and the equivalent Chinese characters was extracted and analyzed based on changes in the frequencies of keywords and hashtags and the Viterbi algorithm. We manually coded a random selection of 5%-7% of the content to identify misinformation on each platform and compared posts using the WHO fact-check page to adjudicate accuracy of content. Results: Both platforms posted about the outbreak and transmission, but posts on Sina Weibo were less likely to reference topics such as WHO, Hong Kong, and death and more likely to cite themes of resisting, fighting, and cheering against coronavirus. Misinformation constituted 1.1% of Twitter content and 0.3% of Sina Weibo content-almost 4 times as much on Twitter compared to Sina Weibo. Conclusions: Quantitative and qualitative analysis of content on both platforms points to lower degrees of misinformation, more content designed to bolster morale, and less reference to topics such as WHO, death, and Hong Kong on Sina Weibo than on Twitter.

The Emotional Anatomy of the Wuhan Lockdown: Sentiment Analysis Using Weibo Data.

BACKGROUND: On January 23, 2020, the city of Wuhan, China, was sealed off in response to the COVID-19 pandemic. Studies have found that the lockdown was associated with both positive and negative emotions, although their findings are not conclusive. In these studies, emotional responses to the Wuhan lockdown were identified using lexicons based on limited emotion types. OBJECTIVE: This study aims to map Chinese people's emotional responses to the Wuhan lockdown and compare Wuhan residents' emotions with those of people elsewhere in China by analyzing social media data from Weibo using a lexicon based on the circumplex model of affect. METHODS: Social media posts on Weibo from 2 weeks before to 2 weeks after the Wuhan lockdown was imposed (January 9, 2020, to February 6, 2020) were collected. Each post was coded using a valence score and an arousal score. To map emotional trajectories during the study period, we used a data set of 359,190 posts. To compare the immediate emotional responses to the lockdown and its longer-term emotional impact on Wuhan residents (n=1236) and non-Hubei residents (n=12,714), we used a second data set of 57,685 posts for multilevel modeling analyses. RESULTS: Most posts (248,757/359,190, 69.25%) made during the studied lockdown period indicated a pleasant mood with low arousal. A gradual increase in both valence and arousal before the lockdown was observed. The posts after the lockdown was imposed had higher valence and arousal than prelockdown posts. On the day of lockdown, the non-Hubei group had a temporarily boosted valence (γ20=0.118; SE 0.021; P<.001) and arousal (γ30=0.293; SE 0.022; P<.001). Compared with non-Hubei residents, the Wuhan group had smaller increases in valence (γ21=-0.172; SE 0.052; P<.001) and arousal (γ31=-0.262; SE 0.053; P<.001) on the day of lockdown. Weibo users' emotional valence (γ40=0.000; SE 0.001; P=.71) and arousal (γ40=0.001; SE 0.001; P=.56) remained stable over the 2 weeks after the lockdown was imposed regardless of geographical location (valence: γ41=-0.004, SE 0.003, and P=.16; arousal: γ41=0.003, SE 0.003, and P=.26). CONCLUSIONS: During the early stages of the pandemic, most Weibo posts indicated a pleasant mood with low arousal. The overall increase in the posts' valence and arousal after the lockdown announcement might indicate collective cohesion and mutual support in web-based communities during a public health crisis. Compared with the temporary increases in valence and arousal of non-Hubei users on the day of lockdown, Wuhan residents' emotions were less affected by the announcement. Overall, our data suggest that Weibo users were not influenced by the lockdown measures in the 2 weeks after the lockdown announcement. Our findings offer policy makers insights into the usefulness of social connections in maintaining the psychological well-being of people affected by a lockdown.

Emoji use in China: popularity patterns and changes due to COVID-19.

Emojis are small pictograms that are frequently embedded within micro-texts to more directly express emotional meanings. To understand the changes in the emoji usage of internet users during the COVID-19 outbreak, we analysed a large dataset collected from Weibo, the most popular Twitter-like social media platform in China, from December 1, 2019, to March 20, 2020. The data contained 38,183,194 microblog posts published by 2,239,472 unique users in Wuhan. We calculated the basic statistics of users' usage of emojis, topics, and sentiments and analysed the temporal patterns of emoji occurrence. After examining the emoji co-occurrence structure, we finally explored other factors that may affect individual emoji usage. We found that the COVID-19 outbreak greatly changed the pattern of emoji usage; i.e., both the proportion of posts containing emojis and the ratio of users using emojis declined substantially, while the number of posts remained the same. The daily proportion of Happy emojis significantly declined to approximately 32%, but the proportions of Sad- and Encouraging-related emojis rose to 24% and 34%, respectively. Despite a significant decrease in the number of nodes and edges in the emoji co-occurrence network, the average degree of the network increased from 34 to 39.8, indicating that the diversity of emoji usage increased. Most interestingly, we found that male users were more inclined towards using regular textual language with fewer emojis after the pandemic, suggesting that during public crises, male groups appeared to control their emotional display. In summary, the COVID-19 pandemic remarkably impacted individual sentiments, and the normal pattern of emoji usage tends to change significantly following a public emergency. Supplementary Information: The online version contains supplementary material available at 10.1007/s10489-022-03195-y.

Differences in User Information Behavior between Official Media and Private Media during the COVID-19 Pandemic.

Weibo is a widely used social media platform showing all kinds of information related to the COVID-19 pandemic promptly in China. Official media and private media are two typical types of media on Weibo. Due to the different characteristics of these two media types, in the context of public health emergencies, it is worth exploring whether there are differences in the users' interactive behavior with information from these two types of media. This is of great significance to the integration and development of these two types of media.This study obtained data on the interaction behaviors of Weibo users with posts published by the two media types at various stages of the pandemic. Statistical analyses have confirmed significant differences in interaction behavior data between users and these two media types. In future research, based on the findings of this study, we will investigate the reasons behind these differences to provide relevant guidelines and suggestions for the release of different media in public health emergencies by conducting a deep dive analysis of user reviews.

Exploring the Factors Associated with Mental Health Attitude in China: A Structural Topic Modeling Approach.

Mental health attitude has huge impacts on the improvement of mental health. In response to the ongoing damage the COVID-19 pandemic caused to the mental health of the Chinese people, this study aims to explore the factors associated with mental health attitude in China. To this end, we extract the key topics in mental health-related microblogs on Weibo, the Chinese equivalent of Twitter, using the structural topic modeling (STM) approach. An interaction term of sentiment polarity and time is put into the STM model to track the evolution of public sentiment towards the key topics over time. Through an in-depth analysis of 146,625 Weibo posts, this study captures 12 topics that are, in turn, classified into four factors as stigma (n = 54,559, 37.21%), mental health literacy (n = 32,199, 21.96%), public promotion (n = 30,747, 20.97%), and social support (n = 29,120, 19.86%). The results show that stigma is the primary factor inducing negative mental health attitudes in China as none of the topics related to this factor are considered positive. Mental health literacy, public promotion, and social support are the factors that could enhance positive attitudes towards mental health, since most of the topics related to these factors are identified as positive ones. The provision of tailored strategies for each of these factors could potentially improve the mental health attitudes of the Chinese people.

Topic Analysis of Public Welfare Microblogs in the Early Period of the COVID-19 Epidemic Based on LDA Model

Due to the outbreak of COVID-19 in early 2020, a flood of information and rumors about the epidemic have filled the internet, causing panic in people’s lives. During the early period of the epidemic, public welfare information with active energy had played a key role in influencing online public opinion, alleviating public anxiety and mobilizing the entire society to fight against the epidemic. Therefore, analyzing the characteristics of public welfare communication in the early period can help us better develop strategies of public welfare communication in the post-epidemic era. In China, Sina Weibo is a microblog platform based on user relationships, and it is widely used by Chinese people. In this paper, we take the public welfare microblogs released by the Weibo public welfare account “@微公益” (Micro public welfare) in the early period of the epidemic as the research object. Firstly, we collected a total of 1863 blog posts from this account from January to April in 2020, and divided them into four stages by combining the Life Cycle Theory. Then the top 10 keywords from the blog posts of different stages were extracted using word frequency statistics. Finally, the LDA topic model were utilized to find out the topics of each stage whose characteristics of public welfare communication were analyzed in detail. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Evolution of Public Sentiments During COVID-19 Pandemic

[Objective] This study analyzes the social media posts during the COVID-19 pandemic, aiming to reveal the temporal and spatial differences of public opinion, the sentiment evolution under different circumstances, as well as the trans-regional spreading of the public sentiments. [Methods] Firstly, we utilized the Latent Dirichlet Allocation (LDA) model to generate the latent topics and related keyword groups, which also analyzed public sentiment evolutions from the perspectives of global and individual topics. Then, we described the trans-regional spread of public sentiments based on the social spread model adapted from the classic Independent Cascade Model. [Results] The new model summarized the general rules of the temporal evolution and spatial difference, as well as the impacts of distance to the epidemic centers and the financial levels. We also found two different types of topics indicating reasons for popularity and sentiment differences, as well as multi-view connections among these topics. The strength of trans-regional sentiment spread could be affected by both regional distance and epidemic situation. [Limitations] The new framework could not process the multimodal data. [Conclusions] The proposed model helps the local government make better strategies according to specific conditions, and pay more attention to the impacts of related events. They should also strengthen regional cooperation and coordination for controlling pandemics and monitoring public sentiments. © 2022, Chinese Academy of Sciences. All rights reserved.