scholarly journals Concerns Expressed by Chinese Social Media Users During the COVID-19 Pandemic: Content Analysis of Sina Weibo Microblogging Data (Preprint)

2020 ◽  
Author(s):  
Junze Wang ◽  
Ying Zhou ◽  
Wei Zhang ◽  
Richard Evans ◽  
Chengyan Zhu
Keyword(s):  
Social Media ◽  
Latent Dirichlet Allocation ◽  
Vaccine Development ◽  
User Behavior ◽  
Chinese Government ◽  
Web Crawler ◽  
Health Crisis ◽  
User Behavior Analysis ◽  
Sina Weibo ◽  
Social Media Platforms

BACKGROUND The COVID-19 pandemic has created a global health crisis that is affecting economies and societies worldwide. During times of uncertainty and unexpected change, people have turned to social media platforms as communication tools and primary information sources. Platforms such as Twitter and Sina Weibo have allowed communities to share discussion and emotional support; they also play important roles for individuals, governments, and organizations in exchanging information and expressing opinions. However, research that studies the main concerns expressed by social media users during the pandemic is limited. OBJECTIVE The aim of this study was to examine the main concerns raised and discussed by citizens on Sina Weibo, the largest social media platform in China, during the COVID-19 pandemic. METHODS We used a web crawler tool and a set of predefined search terms (<i>New Coronavirus Pneumonia</i>, <i>New Coronavirus</i>, and <i>COVID-19</i>) to investigate concerns raised by Sina Weibo users. Textual information and metadata (number of likes, comments, retweets, publishing time, and publishing location) of microblog posts published between December 1, 2019, and July 32, 2020, were collected. After segmenting the words of the collected text, we used a topic modeling technique, latent Dirichlet allocation (LDA), to identify the most common topics posted by users. We analyzed the emotional tendencies of the topics, calculated the proportional distribution of the topics, performed user behavior analysis on the topics using data collected from the number of likes, comments, and retweets, and studied the changes in user concerns and differences in participation between citizens living in different regions of mainland China. RESULTS Based on the 203,191 eligible microblog posts collected, we identified 17 topics and grouped them into 8 themes. These topics were pandemic statistics, domestic epidemic, epidemics in other countries worldwide, COVID-19 treatments, medical resources, economic shock, quarantine and investigation, patients’ outcry for help, work and production resumption, psychological influence, joint prevention and control, material donation, epidemics in neighboring countries, vaccine development, fueling and saluting antiepidemic action, detection, and study resumption. The mean sentiment was positive for 11 topics and negative for 6 topics. The topic with the highest mean of retweets was domestic epidemic, while the topic with the highest mean of likes was quarantine and investigation. CONCLUSIONS Concerns expressed by social media users are highly correlated with the evolution of the global pandemic. During the COVID-19 pandemic, social media has provided a platform for Chinese government departments and organizations to better understand public concerns and demands. Similarly, social media has provided channels to disseminate information about epidemic prevention and has influenced public attitudes and behaviors. Government departments, especially those related to health, can create appropriate policies in a timely manner through monitoring social media platforms to guide public opinion and behavior during epidemics.

scholarly journals Concerns Expressed by Chinese Social Media Users During the COVID-19 Pandemic: Content Analysis of Sina Weibo Microblogging Data

10.2196/22152 ◽  
2020 ◽  
Vol 22 (11) ◽  
pp. e22152
Author(s):  
Junze Wang ◽  
Ying Zhou ◽  
Wei Zhang ◽  
Richard Evans ◽  
Chengyan Zhu
Keyword(s):  
Social Media ◽  
Latent Dirichlet Allocation ◽  
Vaccine Development ◽  
User Behavior ◽  
Chinese Government ◽  
Web Crawler ◽  
Health Crisis ◽  
User Behavior Analysis ◽  
Sina Weibo ◽  
Social Media Platforms

Background The COVID-19 pandemic has created a global health crisis that is affecting economies and societies worldwide. During times of uncertainty and unexpected change, people have turned to social media platforms as communication tools and primary information sources. Platforms such as Twitter and Sina Weibo have allowed communities to share discussion and emotional support; they also play important roles for individuals, governments, and organizations in exchanging information and expressing opinions. However, research that studies the main concerns expressed by social media users during the pandemic is limited. Objective The aim of this study was to examine the main concerns raised and discussed by citizens on Sina Weibo, the largest social media platform in China, during the COVID-19 pandemic. Methods We used a web crawler tool and a set of predefined search terms (New Coronavirus Pneumonia, New Coronavirus, and COVID-19) to investigate concerns raised by Sina Weibo users. Textual information and metadata (number of likes, comments, retweets, publishing time, and publishing location) of microblog posts published between December 1, 2019, and July 32, 2020, were collected. After segmenting the words of the collected text, we used a topic modeling technique, latent Dirichlet allocation (LDA), to identify the most common topics posted by users. We analyzed the emotional tendencies of the topics, calculated the proportional distribution of the topics, performed user behavior analysis on the topics using data collected from the number of likes, comments, and retweets, and studied the changes in user concerns and differences in participation between citizens living in different regions of mainland China. Results Based on the 203,191 eligible microblog posts collected, we identified 17 topics and grouped them into 8 themes. These topics were pandemic statistics, domestic epidemic, epidemics in other countries worldwide, COVID-19 treatments, medical resources, economic shock, quarantine and investigation, patients’ outcry for help, work and production resumption, psychological influence, joint prevention and control, material donation, epidemics in neighboring countries, vaccine development, fueling and saluting antiepidemic action, detection, and study resumption. The mean sentiment was positive for 11 topics and negative for 6 topics. The topic with the highest mean of retweets was domestic epidemic, while the topic with the highest mean of likes was quarantine and investigation. Conclusions Concerns expressed by social media users are highly correlated with the evolution of the global pandemic. During the COVID-19 pandemic, social media has provided a platform for Chinese government departments and organizations to better understand public concerns and demands. Similarly, social media has provided channels to disseminate information about epidemic prevention and has influenced public attitudes and behaviors. Government departments, especially those related to health, can create appropriate policies in a timely manner through monitoring social media platforms to guide public opinion and behavior during epidemics.

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.

Blogging With a Mission, Blogging Within a System: Chinese Government-organized NGOs, Corporate-organized NGOs, Grassroots, and Student Organizations on Weibo

2017 ◽  
Vol 22 (3) ◽  
pp. 95-119 ◽  
Author(s):  
Huiquan Zhou ◽  
Quanxiao Pan
Keyword(s):  
Information Technology ◽  
Social Media ◽  
Rural Education ◽  
Nongovernmental Organizations ◽  
Student Organizations ◽  
Chinese Government ◽  
Sina Weibo ◽  
Organizational Information ◽  
Social Media Platforms ◽  
Update Frequency

By analyzing 155 rural education nongovernmental organizations’ posting behavior on one of China’s largest social media platforms, Sina Weibo, we show that organizations with different backgrounds (government, corporate, grassroots, and student) behave differently. While organizational information technology capacity influences update frequency, organizational background influences the preference for informational, dialogic, or promotional posts.

An Experimental Study of Spammer Detection on Chinese Microblogs

2020 ◽  
Vol 30 (11n12) ◽  
pp. 1759-1777
Author(s):  
Jialing Liang ◽  
Peiquan Jin ◽  
Lin Mu ◽  
Jie Zhao
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
User Behavior ◽  
Real Data ◽  
User Profile ◽  
Data Set ◽  
Sina Weibo ◽  
Factors Affecting ◽  
The Government ◽  
Hot Event

With the development of Web 2.0, social media such as Twitter and Sina Weibo have become an essential platform for disseminating hot events. Simultaneously, due to the free policy of microblogging services, users can post user-generated content freely on microblogging platforms. Accordingly, more and more hot events on microblogging platforms have been labeled as spammers. Spammers will not only hurt the healthy development of social media but also introduce many economic and social problems. Therefore, the government and enterprises must distinguish whether a hot event on microblogging platforms is a spammer or is a naturally-developing event. In this paper, we focus on the hot event list on Sina Weibo and collect the relevant microblogs of each hot event to study the detecting methods of spammers. Notably, we develop an integral feature set consisting of user profile, user behavior, and user relationships to reflect various factors affecting the detection of spammers. Then, we employ typical machine learning methods to conduct extensive experiments on detecting spammers. We use a real data set crawled from the most prominent Chinese microblogging platform, Sina Weibo, and evaluate the performance of 10 machine learning models with five sampling methods. The results in terms of various metrics show that the Random Forest model and the over-sampling method achieve the best accuracy in detecting spammers and non-spammers.

Customer Experience: Extracting Topics From Tweets

2021 ◽  
pp. 147078532110475
Author(s):  
Manit Mishra
Keyword(s):  
Social Media ◽  
Customer Service ◽  
Latent Dirichlet Allocation ◽  
Online Shopping ◽  
Customer Experience ◽  
Process Failure ◽  
Shopping Experience ◽  
Social Media Platforms ◽  
Media Platform ◽  
Moments Of Truth

The ubiquity of social media platforms facilitates free flow of online chatter related to customer experience. Twitter is a prominent social media platform for sharing experiences, and e-retail firms are rapidly emerging as the preferred shopping destination. This study explores customers’ online shopping experience tweets. Customers tweet about their online shopping experience based on moments of truth shaped by encounters across different touchpoints. We aggregate 25,173 such tweets related to six e-retailers tweeted over a 5-year period. Grounded on agency theory, we extract the topics underlying these customer experience tweets using unsupervised latent Dirichlet allocation. The output reveals five topics which manifest into customer experience tweets related to online shopping—ordering, customer service interaction, entertainment, service outcome failure, and service process failure. Topics extracted are validated through inter-rater agreement with human experts. The study, thus, derives topics from tweets about e-retail customer experience and thereby facilitates prioritization of decision-making pertaining to critical service encounter touchpoints.

A Comparative View of Censored and Uncensored Political Discussion

2017 ◽  
pp. 269-282
Author(s):  
Qihao Ji
Keyword(s):  
Social Media ◽  
Content Analysis ◽  
Future Research ◽  
Chinese Government ◽  
Political Discussion ◽  
Time Period ◽  
Social Media Platforms ◽  
Internet Censorship ◽  
Media Discourses ◽  
The Impact

Through a content analysis on Chinese online dissidents' social media discourses, this study examines the impact of Internet censorship on Chinese dissidents' political discourse in two social media platforms: Weibo and Twitter. Data was collected during a time period when China's Internet censorship was tightened. Results revealed that Chinese online dissidents are more likely to post critical opinions and direct criticism towards the Chinese government on Twitter. In addition, dissidents on Twitter are more likely to engage in discussing with others, while Weibo dissidents tend to adopt linguistic skills more often to bypass censorship. No difference was found in terms of dissidents' civility and rationality across the two platforms. Implications and future research are discussed in detail.

scholarly journals Bonding across Chinese social media

Pragmatics ◽  
2020 ◽  
Vol 30 (3) ◽  
pp. 431-457 ◽  
Author(s):  
Chaoqun Xie ◽  
Ying Tong ◽  
Francisco Yus
Keyword(s):  
Social Media ◽  
Virtual Community ◽  
Social Bonding ◽  
Social Functions ◽  
Sina Weibo ◽  
Language Play ◽  
Community Values ◽  
Virtual Community Of Practice ◽  
Social Media Platforms ◽  
Linguistic Behavior

Abstract This paper explores social bonding in language play via the construction of ‘Chinese character (annotation)’ on two major social media platforms (Sina Weibo and WeChat) in China. The Chinese characters and their bracketed annotations under study, despite their one-to-one matching in sequence, never match each other either in meaning or in pronunciation. They convey a sense of playfulness among social media users who may be acquaintances or strangers to each other. While research on language play has uncovered systematic interpersonal meanings and social functions, our analysis of screen-based and user-based data shows that such linguistic behavior in a virtual community of practice contributes to social bonding among social media players. Within such structure and with different substitutes for both characters and annotations, social media users frame their expressions in evaluative or emotive ways to facilitate their presentation of an alternative self and of individual or community values.

scholarly journals A Rights-Based Approach to Trustworthy AI in Social Media

2020 ◽  
Vol 6 (3) ◽  
pp. 205630512095467
Author(s):  
Dave Lewis ◽  
Joss Moorkens
Keyword(s):  
Social Media ◽  
User Behavior ◽  
Self Regulation ◽  
Digital Content ◽  
Virtual Agents ◽  
Data Governance ◽  
Physical Context ◽  
Data Ownership ◽  
Social Media Platforms ◽  
Institutional Analysis And Development

Social media platforms increasingly use powerful artificial intelligence (AI) that are fed by the vast flows of digital content that may be used to analyze user behavior, mental state, and physical context. New forms of AI-generated content and AI-driven virtual agents present new forms of risks in social media use, the harm of which will be difficult to predict. Delivering trustworthy social media will therefore be increasingly predicated on effectively governing the trustworthiness of its AI components. In this article, we examine different approaches to the governance AI and the Big Data processing that drives it being explored. We identify a potential over-reliance on individual rights at the expense of consideration of collective rights. In response, we propose a collective approach to AI data governance grounded in a legal proposal for universal, non-exclusive data ownership right. We use the Institutional Analysis and Development (IAD) framework to explore the relative costs and benefits on stakeholders in two use cases, one focused on digital content consumers the other focused on digital content knowledge workers. Following an analysis that looks at self-regulation and industry-state co-regulation, we propose governance through shared data ownership. In this way, future social media platforms may be able to maintain trust in their use of AI by committing to no datafication without representation.

Curbing profanity online: A network-based diffusion analysis of profane speech on Chinese social media

2020 ◽  
pp. 146144482090506
Author(s):  
Yunya Song ◽  
K Hazel Kwon ◽  
Jianliang Xu ◽  
Xin Huang ◽  
Shiying Li
Keyword(s):  
Social Media ◽  
Computational Methods ◽  
State Government ◽  
Diffusion Processes ◽  
Sina Weibo ◽  
Digital Space ◽  
Diffusion Analysis ◽  
Social Media Platforms ◽  
Structural Metrics ◽  
Chinese Social Media

Profanity, also known as swearing, refers to the use of foul language that is often linked to incivility. In Chinese digital space, the state government actively censors profanity under the rationale of protecting online civility. This study examines the diffusion of profanity in Sina Weibo, one of the largest Chinese social media platforms. The study applied computational methods to reconstruct the cascade networks of swearing and non-swearing posts and analyzed the network diffusion processes based on a set of structural metrics including reposting depth, width, and interlayer width ratios. Findings suggest profanity may influence the process of message diffusion, but this effect was ephemeral. Based on the understanding of diffusion processes of profanity online, this study contends the viral potential of profanity may not be as severe as the regulators claim. The discussion analyzes the extent to which content moderation efforts are necessary for the nurturing of civility online.

scholarly journals Understanding user satisfaction with Chinese government social media platforms

2020 ◽  
Author(s):  
Feng Yang ◽  
◽  
Shan Zhao ◽  
Wenyong Li ◽  
Richard Evans ◽  
...  
Keyword(s):  
Social Media ◽  
User Satisfaction ◽  
Structural Equation ◽  
Online Survey ◽  
Positive Influence ◽  
Survey Study ◽  
Chinese Government ◽  
Study Results ◽  
Social Media Platforms ◽  
The Government

Introduction. The purpose of this paper is to understand government social media from the perspective of user satisfaction and to evaluate it in the context of presentation, content and utility of the government affairs' microblogs in China. Method. Based on the comprehensive information theory, this study will generalise descriptions about the factors affecting the user satisfaction in the existing research. Analysis. Taking Chinese government affairs microblogs as examples, the paper utilises structural equation modelling to analyse an online survey study. Results. Its result indicates that presentation, content and utility have a positive influence on user satisfaction with Chinese government social media platforms. Conclusions. This study gets rid of the oversimplified description of the application of government social media, and could provide policy reference for subsequent adoption strategies of government social media.

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