scholarly journals Emotional Attitudes of Chinese Citizens on Social Distancing During the COVID-19 Outbreak: Analysis of Social Media Data

10.2196/27079 ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. e27079
Author(s):  
Lining Shen ◽  
Rui Yao ◽  
Wenli Zhang ◽  
Richard Evans ◽  
Guang Cao ◽  
...  
Keyword(s):  
Social Media ◽  
Goodness Of Fit ◽  
Negative Emotions ◽  
Hubei Province ◽  
Moderating Effect ◽  
Sina Weibo ◽  
Social Distancing ◽  
Explanatory Variables ◽  
Travel Restrictions ◽  
The Impact

Background Wuhan, China, the epicenter of the COVID-19 pandemic, imposed citywide lockdown measures on January 23, 2020. Neighboring cities in Hubei Province followed suit with the government enforcing social distancing measures to restrict the spread of the disease throughout the province. Few studies have examined the emotional attitudes of citizens as expressed on social media toward the imposed social distancing measures and the factors that affected their emotions. Objective The aim of this study was twofold. First, we aimed to detect the emotional attitudes of different groups of users on Sina Weibo toward the social distancing measures imposed by the People’s Government of Hubei Province. Second, the influencing factors of their emotions, as well as the impact of the imposed measures on users’ emotions, was studied. Methods Sina Weibo, one of China’s largest social media platforms, was chosen as the primary data source. The time span of selected data was from January 21, 2020, to March 24, 2020, while analysis was completed in late June 2020. Bi-directional long short-term memory (Bi-LSTM) was used to analyze users’ emotions, while logistic regression analysis was employed to explore the influence of explanatory variables on users’ emotions, such as age and spatial location. Further, the moderating effects of social distancing measures on the relationship between user characteristics and users’ emotions were assessed by observing the interaction effects between the measures and explanatory variables. Results Based on the 63,169 comments obtained, we identified six topics of discussion—(1) delaying the resumption of work and school, (2) travel restrictions, (3) traffic restrictions, (4) extending the Lunar New Year holiday, (5) closing public spaces, and (6) community containment. There was no multicollinearity in the data during statistical analysis; the Hosmer-Lemeshow goodness-of-fit was 0.24 (χ28=10.34, P>.24). The main emotions shown by citizens were negative, including anger and fear. Users located in Hubei Province showed the highest amount of negative emotions in Mainland China. There are statistically significant differences in the distribution of emotional polarity between social distancing measures (χ220=19,084.73, P<.001), as well as emotional polarity between genders (χ24=1784.59, P<.001) and emotional polarity between spatial locations (χ24=1659.67, P<.001). Compared with other types of social distancing measures, the measures of delaying the resumption of work and school or travel restrictions mainly had a positive moderating effect on public emotion, while traffic restrictions or community containment had a negative moderating effect on public emotion. Conclusions Findings provide a reference point for the adoption of epidemic prevention and control measures, and are considered helpful for government agencies to take timely actions to alleviate negative emotions during public health emergencies.

scholarly journals Social Distancing in the Hubei Province: Emotional Attitudes of Chinese citizens at the Outbreak of COVID-19 (Preprint)

2021 ◽  
Author(s):  
Lining Shen ◽  
Rui Yao ◽  
Wenli Zhang ◽  
Richard Evans ◽  
Guang Cao
Keyword(s):  
Social Media ◽  
Positive Emotions ◽  
Hubei Province ◽  
Moderating Effects ◽  
User Characteristics ◽  
Sina Weibo ◽  
Social Distancing ◽  
The Social ◽  
Social Media Platforms ◽  
The Relationship

BACKGROUND Wuhan, the epicenter of the COVID-19 outbreak, imposed citywide lockdown measures on 23 January 2020. Neighboring cities in the Hubei province followed suit with the government enforcing social distancing measures to restrict the spread of the disease throughout the province. Few studies have examined the emotional attitudes of citizens on social media platforms towards the imposed social distancing measures, and the factors that affected their emotions. OBJECTIVE The aim of this study is twofold. First, we detect the emotional attitudes of different groups of Sina Weibo users towards the social distancing measures imposed by the Peoples Government of Hubei Province. Second, we study the influencing factors of their emotions as well as the impact of imposed measures on users' emotions. METHODS Sina Weibo, one of China's largest social media platforms, was chosen as the primary data source. Bi-directional Long Short-Term Memory (Bi-LSTM) was used to analyze users' emotions, while logistic regression analysis was employed to explore the influence of independent variables on users' emotions, such as age and spatial locations. Further, the moderating effects of social distancing measures on the relationship between user characteristics and users' emotions are discussed through the interaction effects between the measures and independent variables. RESULTS We identified six topics of discussion, including delaying the resumption of work and school, travel restrictions, traffic restrictions, extending the Lunar New Year holiday, closing public spaces, and community containment. First, the main emotions shown by citizens were negative, including anger and fear. Women were observed to hold stronger and more positive emotions than men. Users located in the Hubei Province showed the highest amount of negative emotions in Mainland China. In addition, those who lived in emigrant provinces, or those with a high number of follows and / or posts, were inclined to express positive emotions. Older users and those with more fans were inclined to be neutral, while users in the Hubei Province, and with a longer registration time on the Sina Weibo platform, were more likely to express negative emotions. Further, different social distancing measures had unalike moderating effects on the relationship between user characteristics and users' emotions. CONCLUSIONS This study identified the emotional attitudes of Sina Weibo users towards the social distancing measures imposed by the Peoples Government of Hubei Province, and determined the characteristics that affect users' emotions, including the factor of social distancing measures. The results provide government agencies with better understanding of Internet users opinions on related events, and provide a reference point for social media platforms to push targeted content.

IMPACT OF THE CORONAVIRUS PANDEMIC ON THE LEVEL OF INFLATION IN THE GLOBAL ECONOMY

2021 ◽  
Vol 3 (11) ◽  
pp. 245-250
Author(s):  
A. Rasha ◽  
◽  
Sergey P. Koltchin ◽  
Keyword(s):  
Global Economy ◽  
Social Distancing ◽  
The World ◽  
Travel Restrictions ◽  
The Impact

The COVID-19 pandemic has prompted many countries to implement social distancing, lock-downs and travel restrictions, bringing the global economy to an unprecedented collapse in peacetime. The article examines the impact of this collapse on the level of inflation in the global economy with some examples of countries in the world.

Who is Setting Emotions? A Comparative Study on Emotion Diffusion in Social Media among Public, Government and Media during the COVID-19 Pandemic in China (Preprint)

2021 ◽  
Author(s):  
Shuhuan Zhou ◽  
Yi Wang
Keyword(s):  
Social Media ◽  
Information Exchange ◽  
Positive Emotions ◽  
Negative Emotions ◽  
Chinese Government ◽  
The Public ◽  
The Media ◽  
The Government ◽  
The Impact ◽  
Time Point

BACKGROUND During the COVID-19 outbreak, social media served as the main platform for information exchange, through which the Chinese government, media and public would spread information. At the same time, a variety of emotions interweave, and the public emotions would also be affected by the government and media. OBJECTIVE This study aims to investigate the types, trends and relationships of emotional diffusion in Chinese social media among the public, the government and the media under the pandemic of COVID-19 (December 30,2019, to July 1,2020) . METHODS In this paper, Python 3.7.0 and its data crawling framework Scrapy 1.5.1 are used to write a web crawler program to search for super topics related to COVID-19 on Sina Weibo platform of different keywords . Then, we used emotional lexicon to analyze the types and trends of the public, government and media emotions on social media. Finally cross-lagged regression was applied to build the relationships of different subjects’ emotions. RESULTS The highlights of our study are threefold: (1) The public, the government and the media mainly diffuse positive emotions during the COVID-19 pandemic in China; (2) Emotional diffusion shows a certain change over time, and negative emotions are obvious in the initial phase of the pandemic, with the development of the pandemic, positive emotions surpass negative emotions and remain stable. (3)The impact among the three main emotions with the period as the time point is weak, while the impact of emotion with the day as the time point is relatively obvious. The emotions of the public and the government impact each other, and the media emotions can guide the public emotions. CONCLUSIONS This is the first study of comparing pubic, government and media emotions on the social media during COVID-19 pandemic in China. The pubic, the government and the media mainly diffuse positive emotions during the pandemic. And the government and the media have better effect on short-term emotional guidance. Therefore, when the pandemic suddenly occurs, the government and the media should intervene in time to solve problems and conflicts and diffuse positive and neutral emotions. In this regard, the government and the media can play important roles through social media in the major outbreaks. At the theoretical level, this paper takes China's epidemic environment and social media as the background to provide one of the explanatory perspectives for the spread of emotions on social media. At the some time, because of this special background, it can provide comparison and reference for the research on internet emotions in other countries.

scholarly journals Mining and Validating Social Media for COVID-19-Related Human Behaviors between January and July; An Infodemiology Study (Preprint)

2021 ◽  
Author(s):  
Ashlynn R. Daughton ◽  
Courtney Diane Shelley ◽  
Martha Barnard ◽  
Dax Gerts ◽  
Chrysm Watson Ross ◽  
...  
Keyword(s):  
Public Health ◽  
Social Media ◽  
Ground Truth ◽  
The United States ◽  
Training Data ◽  
Long Term Effects ◽  
Social Distancing ◽  
Human Behaviors ◽  
Mobility Data ◽  
The Impact

BACKGROUND Health authorities can minimize the impact of an emergent infectious disease outbreak through effective and timely risk communication, which can build trust and adherence to subsequent behavioral messaging. Monitoring the psychological impacts of an outbreak, as well as public adherence to such messaging is also important for minimizing long term effects of an outbreak. OBJECTIVE We used social media data to identify human behaviors relevant to COVID-19 transmission and the perceived impacts of COVID-19 on individuals as a first step toward real time monitoring of public perceptions to inform public health communications. METHODS We develop a coding schema for 6 categories and 11 subcategories, which includes both a wide number of behaviors, as well codes focused on the impacts of the pandemic (e.g., economic and mental health impacts). We use this to develop training data and develop supervised learning classifiers for classes with sufficient labels. Classifiers that perform adequately are applied to our remaining corpus and temporal and geospatial trends are assessed. We compare the classified patterns to ground truth mobility data and actual COVID-19 confirmed cases to assess the signal achieved here. RESULTS We apply our labeling schema to ~7200 tweets. The worst performing classifiers have F1 scores of only 0.18-0.28 when trying to identify tweets about monitoring symptoms and testing. Classifiers about social distancing, however, are much stronger with F1 scores of 0.64-0.66. We applied the social distancing classifiers to over 228 million tweets. We show temporal patterns consistent with real-world events, and show correlations of up to -0.5 between social distancing signals on Twitter and ground-truth mobility throughout the United States. CONCLUSIONS Behaviors discussed on Twitter are exceptionally varied. Twitter can provide useful information for parameterizing models that incorporate human behavior as well as informing public health communication strategies by describing awareness of and compliance with suggested behaviors. CLINICALTRIAL N/A

scholarly journals Synchronized travel restrictions across cities can be effective in COVID-19 control

2020 ◽  
Author(s):  
Haiyan Liu ◽  
Xuemei Bai ◽  
Huanfeng Shen ◽  
Xiaoping Pang ◽  
Zeyu Liang ◽  
...  
Keyword(s):  
Hubei Province ◽  
Mobility Patterns ◽  
Chinese Cities ◽  
The Third ◽  
Travel Restrictions ◽  
The Impact

AbstractThe COVID-19 outbreak is under control in China. Mobility interventions, including both the Wuhan lockdown and travel restrictions in other cities, have been undertaken in China to mitigate the epidemic. However, the impact of mobility restrictions in cites outside Wuhan has not been systematically analyzed. Here we ascertain the relationships between all mobility patterns and the epidemic trajectory in Chinese cities outside Hubei Province, and we estimate the impact of local travel restrictions. We estimate local inter-city travel bans averted 22.4% (95% PI: 16.8–27.9%) more infections in the two weeks after the Wuhan lockdown, while local intra-city travel prevented 32.5% (95% PI: 18.9–46.1%) more infections in the third and fourth weeks. More synchronized implementation of mobility interventions would further decrease the number of confirmed cases in the first two weeks by 15.7% (95% PI:15.4–16.0%). This study shows synchronized travel restrictions across cities can be effective in COVID-19 control.

scholarly journals Social Media Behavior and Emotional Evolution during Emergency Events

Healthcare ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 1109
Author(s):  
Mingyun Gu ◽  
Haixiang Guo ◽  
Jun Zhuang
Keyword(s):  
Social Media ◽  
Online Social Networks ◽  
User Behavior ◽  
Social Emotional ◽  
Critical Function ◽  
Sina Weibo ◽  
Emergency Event ◽  
Social Media Platforms ◽  
New Perspective ◽  
The Impact

Online social networks have recently become a vital source for emergency event news and the consequent venting of emotions. However, knowledge on what drives user emotion and behavioral responses to emergency event developments are still limited. Therefore, unlike previous studies that have only explored trending themes and public sentiment in social media, this study sought to develop a holistic framework to assess the impact of emergency developments on emotions and behavior by exploring the evolution of trending themes and public sentiments in social media posts as a focal event developed. By examining the event timelines and the associated hashtags on the popular Chinese social media site Sina-Weibo, the 2019 Wuxi viaduct collapse accident was taken as the research object and the event timeline and the Sina-Weibo tagging function focused on to analyze the behaviors and emotional changes in the social media users and elucidate the correlations. It can conclude that: (i) There were some social media rules being adhered to and that new focused news from the same event impacted user behavior and the popularity of previous thematic discussions. (ii) While the most critical function for users appeared to express their emotions, the user foci changed when recent focus news emerged. (iii) As the news of the collapse deepened, the change in user sentiment was found to be positively correlated with the information released by personal-authentication accounts. This research provides a new perspective on the extraction of information from social media platforms in emergencies and social-emotional transmission rules.

scholarly journals The Moderating Effect of ‘Generation’ on the Relations between Source Credibility of Social Media Contents, Hotel Brand Image, and Purchase Intention

2021 ◽  
Vol 13 (16) ◽  
pp. 9471
Author(s):  
Hye-Ryeong Shin ◽  
Jeong-Gil Choi
Keyword(s):  
Social Media ◽  
Generational Differences ◽  
Purchase Intention ◽  
Source Credibility ◽  
Brand Image ◽  
Group Analysis ◽  
Moderating Effect ◽  
Media Communication ◽  
Social Media Communication ◽  
The Impact

This is a timely study that simultaneously considers the issues of source credibility of social media contents and generational differences. The study aims to explore the influence of ‘generation’ on perceived source credibility, and its effect on the relation between source credibility, hotel brand image, and purchase intention in cases where the content providers are general users (UGCs) and hotel marketers (MGCs), respectively. Using an independent samples t-test (278 people sampled), the differences in source credibility between generations were tested and multi-group analysis was conducted to verify the moderating effect of generation. Significant differences appeared in trustworthiness between the generations. Millennials are sharper in observation than the generations born earlier in recognizing the source credibility of social media contents. The moderating effect of generation is noticeable only in the impact of the UGCs’ expertise on hotel brand image, indicating Millennials are affected by the expertise of UGCs more strongly than the earlier generations are. The findings offer insight into better strategizing of social media communication for hotel marketers, utilizing social media and targeting Millennials. A further contribution of the study is that it reveals the relations between variables and effects according to different content providers (UGCs and MGCs).

Organic food consumerism through social commerce in China

2019 ◽  
Vol 31 (1) ◽  
pp. 202-222 ◽  
Author(s):  
Anum Tariq ◽  
Changfeng Wang ◽  
Yasir Tanveer ◽  
Umair Akram ◽  
Zubair Akram
Keyword(s):  
Social Media ◽  
Visual Information ◽  
Online Survey ◽  
Organic Food ◽  
Moderating Effect ◽  
Impulse Buying ◽  
Social Commerce ◽  
Content Type ◽  
Website Features ◽  
The Impact

PurposeThe purpose of this paper is to examine the impact of consumers’ attitudes towards organic food on online impulse buying behaviour as well as the moderating effect of three website features (visual, information and navigation design) on this relationship.Design/methodology/approachSurvey data were collected via an online survey using social media platforms. A total of 653 online questionnaires were collected (response rate = 72.5 per cent) and analysed by applying exploratory and confirmatory factor analyses. The proposed hypotheses were tested through structural equation modelling.FindingsSocial media forums, ratings and reviews shape Chinese consumers’ attitudes towards organic food and positively influence their online impulse buying in this market. Website features are critical for disseminating information on organic food. Informative webpages featuring product quality and certification have a greater moderating effect on purchase. Information cues such as nutritional content; production and processing methods, and environmentally friendliness also influence consumers’ attitudes and thus impulse buying decisions.Practical implicationsMarketers should reconsider their tactics for dealing with modern consumers, as webpages should be user-friendly and visually appealing with a social learning mechanism to drive organic food consumption.Originality/valueThis study bridges a gap in the literature on social commerce initiatives for developing consumers’ attitudes towards organic food and online impulse buying. Further, it proposes measures that can enhance organic consumption and contributes to the literature on the importance of social factors, resulting in enhanced knowledge on the online impulse buying of organic food.

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