Online Rumors Research Articles

Spreading online rumours during the COVID-19 pandemic: the role of users’ knowledge, trust and emotions as predictors of the spreading patterns

ABSTRACT The COVID-19 pandemic has generated severe social, economic, and political implications and challenges in addition to unprecedented health threats and harm. A typical phenomenon associated with emergencies and crises is the spreading of rumours. Social networks have become a popular arena for spreading rumours in various contexts, including during the COVID-19 pandemic. This study analysed the circumstances under which people might spread such rumours and the psychological mechanism behind this behaviour. We examined potential factors that might influence the spreading of pandemic-related online rumours (behavioural component): the participants’ thoughts and beliefs about the rumour (cognitive component), users’ trust in the information to which they are exposed by the media (trust component), and the emotional response to information regarding the epidemic resulting from media exposure (emotional component). Using a survey of individuals who were exposed to COVID-19 rumours, we could test the effects of our independent variables on the willingness to spread the rumours. Research findings indicate that there is a correlation between the cognitive component and the behavioural component. We also identified a mediated route of influence through the trust component. Contrary to our hypothesis, we didn't find that the emotional component was a mediator between the cognitive and behavioural components.

Exploring rumor combating behavior of social media on NIMBY conflict: Temporal modes, frameworks and strategies

With the development of social media, mass unreliable information is circulated which amplifies the impact on NIMBY conflict, which is caused by public concern about the negative externalities of development projects. Understanding the behavior of rumor combating provides significant insights for crisis management relating to public acceptance of large-scale infrastructure initiatives, construction projects or energy facilities. However, few studies have addressed how rumor combating behavior develops due to the online rumors in such crises. Accordingly, this study aimed to investigate the formation and the effect of rumor combating behavior on NIMBY conflict with the analytical framework by content analysis and curve fitting method based on Situational Crisis Communication Theory. In this framework, the temporal modes and frameworks evolution of the counter-rumors are illustrated, the influences and behaviors tendency of multiple rumor refuters are examined, and the effects of the rumor combating strategies are explored via acceptance analysis. The results show that there are two key diffusion cycles in the progress of rumor combating, and early counter-rumors can pre-emptively protect the users' attitude. The interactive features of the framework between rumors and counter-rumors vary at different stages and an Assessment framework can provide a quick response to combat rumors. In addition, Media practitioners and News organizations act as the bellwether in rumor combating action, while Individuals and Elites are the main forces as the rumor refuters. Refutation and Guide, fact-based rumor combating strategies, show great persuasive impact. These findings will help the government and relevant entities to implement rumor combating strategies to minimize the potential exacerbation of NIMBY conflict.

COVID-19-related information seeking and individual's rumor refuting: A multi-information-source perspective

Existing literatures of rumor on social media mainly focus on its sharing, ignoring rumor refuting related studies. To bridge the above research gap, present study proposed a dual-pathway model examining the impact of different information-source on online rumor refuting. Specially, COVID-19-related information seeking will induce individuals' rumor refuting, among which individuals’ health self-efficacy and infection risk perception play the mediating role. Meanwhile, peer condition and peer communication moderate the above two pathways. Data from 4596 individuals to a large online survey support our theoretical model. Our framework contributes to both theory and practice.

The Effects of Personality Traits on Online Rumor Sharing: The Mediating Role of Fear of COVID-19.

This study aims to explore the effects of personality traits on online rumor sharing during the novel coronavirus (COVID-19) pandemic and the mediating role of the fear of COVID-19 between them. We conducted this research using a web-based questionnaire distributed to 452 university students who were invited to fill it out. The partial least square structural equation modeling (PLS-SEM) method was used to test the data and model, with the yielded results demonstrating that three—extroversion, emotional instability, and conscientiousness—of the Big Five personality traits are positively related to a fear of COVID-19, with this fear positively affecting online rumor sharing. Moreover, fear of COVID-19 was found to act as a mediator between personality traits and online rumor sharing; thus, we can conclude that persons with high levels of extroversion, emotional instability, and conscientiousness are more likely to share rumors online due to a fear of COVID-19. This study furthers our understanding of the psychological mechanism by which personality traits influence online rumor sharing and provides references for anti-rumor campaigns taking place during the COVID-19 pandemic, as it identifies key groups and sheds light on the necessity of reducing people’s fear of COVID-19.

Internet Rumor Audience Response Prediction Algorithm Based on Machine Learning in Big Data Environment

Rumors are an important factor affecting social stability in some special times. Therefore, the dissemination and prevention and control mechanisms of rumors have always been issues of concern to the academic community and have long been highly valued and widely discussed by experts and scholars. However, in combination with the Internet as a new type of media, although people have begun to pay attention to online rumors, research on it is still relatively fragmented, especially in the cross-domain research specific to the social influence of online rumors, and there is no clear indication of online rumors. The specific definition also did not analyze in detail the internal connection between its influence and group behavior. Therefore, this article will combine actual cases to explore and analyze the spread and influence process of online rumors and show its social influence, hoping to enrich the research of online rumors. Nowadays, the Internet has become the most important carrier to reflect the public grievances. Internet users have expressed their opinions on hot issues such as enterprises, people’s livelihood, and government management, which has formed a powerful public opinion pressure, which has far exceeded the traditional media. The hidden dangers of security cannot be ignored. Therefore, how to monitor network public opinion from a large amount of network data is a difficult problem that needs to be solved urgently. Firstly, this consists of four modules: information collection, web page preprocessing, public opinion analysis, and public information report. Secondly, text clustering, the core technology of network public opinion, is optimized, and single-pass algorithm based on double threshold is proposed. Then the dual-threshold single-pass algorithm is optimized based on the MapReduce parallel computing model, and finally a network public opinion collection technology is formed under the background of big data. Simulation results can greatly improve the performance of text clustering and can effectively optimize the design using the parallel computing model based on MapReduce. The average miss rate after optimization is 0.7569 times, the average false alarm rate is 0.5556 times, and C det is 0.5714 times. It proves that the collection technology based on machine learning under the background of big data is effective and has good performance.

Research on the Communication Mechanism of Online Rumors Under the Empowerment of New Media Technology—Take the “Nabobess Having an Affair With Courier” Rumor Incident as an Example

Research on the Communication Mechanism of Online Rumors Under the Empowerment of New Media Technology—Take the “Nabobess Having an Affair With Courier” Rumor Incident as an Example

Study on the Criminal Law Regulation of Online Rumors Insulting "Strangers"

According to the annual legal supervision cases released by the Supreme People's Court of the People's Republic of China in recent years, the online rumors insulting strangers based on their characteristics, which damages the strangers' reputation, will be identified as crime of defamation. The criminal law regulation is significant in this regard, and based on the certain civil liability system, this act should be defined as crime of defamation since it infringes people's fame and dignity. As for the infringement of legal interests, the act of starting a rumor, in essence, matches with the definition of the crime of picking quarrels and provoking trouble, which refers to those acts of fabricating and intentionally spreading false information and seriously disturbing social order. When both the indictment criteria for defamation and the criterion of serious disruption of public order are met, the imaginative joinder offenses arise.

Social Public Opinion Communication and Network Legal Management Based on Artificial Intelligence Cognitive Wireless Network

Public opinion supervision is an important part of the national security supervision system. In the Internet era, especially with the rapid development of mobile social media, the position of online public opinion supervision in public opinion supervision is becoming more and more prominent. Internet public opinion supervision has a wide range of subjects, diverse objects, multiple channels, instant and efficient communication speed, and two-way interaction and has its distinctive features, but at the same time there are phenomena such as online rumors, invasion of others' privacy, and venting private anger. The existence of these problems requires strengthening the legal system of public opinion supervision, enhancing the network literacy of Internet users, government management departments, website operators, and other subjects of online public opinion supervision, continuously improving the technical level of online public opinion monitoring, and public opinion guidance ability of network supervision departments, and strengthening the regulation of online public opinion supervision through the improvement and improvement of legal system and coordinated promotion of cyberspace governance. Meanwhile, mobile Internet is the soil for social opinion dissemination. With the development of technology, cognitive wireless network is becoming an important infrastructure in the mobile Internet. Therefore, this paper studies social opinion dissemination and cyber law management in cognitive wireless networks and proposes a cognitive engine model based on artificial intelligence algorithms for cognitive wireless networks for enhancing opinion dissemination and law management. The extended experiments demonstrate the advanced performance and effectiveness of the proposed method in this paper and provide a new technical approach for enhancing public opinion dissemination and legal management.

Critical Pragmatic Analysis on the Title of Online Rumors on COVID-19

The rapid development of the network brings convenience to information exchange as well as adds fuel to rumor mongering. During the outbreak of COVID-19 in early 2020, a large number of online rumors associated with the epidemic also emerged, which penetrated throughout the country at a very rapid rate through microblogs, online forums, social networking sites and other online platforms, causing a significant negative impact. In order to help foster a good online environment, this paper studies the titles of online rumors generated during the epidemic, discusses the characteristics of the words, appellations used in the titles under the guidance of Critical Pragmatics, and explores the reasons why online rumors affect the ideology of netizens. Finally, according to the key words, three types of rumor titles are summarized. They are respectively information type, incentive type and argument type. It is hoped that this study can help people better identify online rumors and build a harmonious network society.

Online Rumor Diffusion Model Based on Variation and Silence Phenomenon in the Context of COVID-19.

In the era of mobile internet, information dissemination has made a new leap in speed and in breadth. With the outbreak of the coronavirus disease 2019 (COVID-19), the COVID-19 rumor diffusion that is not limited by time and by space often becomes extremely complex and fickle. It is also normal that a piece of unsubstantiated news about COVID-19 could develop to many versions. We focus on the stagnant role and information variants in the process of rumor diffusion about COVID-19, and through the study of variability and silence in the dissemination, which combines the effects of stagnation phenomenon and information variation on the whole communication system in the circulation of rumors about COVID-19, based on the classic rumor SIR (Susceptible Infected Recovered) model, we introduce a new concept of “variation” and “oyster”. The stability of the new model is analyzed by the mean field equation, and the threshold of COVID-19 rumor propagation is obtained later. According to the results of the simulation experiment, whether in the small world network or in the scale-free network, the increase of the immure and the silent probability of the variation can effectively reduce the speed of rumor diffusion about COVID-19 and is conducive to the dissemination of the truth in the whole population. Studies have also shown that increasing the silence rate of variation can reduce COVID-19 rumor transmission more quickly than the immunization rate. The interesting discovery is that at the same time, a higher rumor infection rate can bring more rumors about COVID-19 but does not always maintain a high number of the variation which could reduce variant tendency of rumors. The more information diffuses in the social group, the more consistent the version and content of the information will be, which proves that the more adequate each individual information is, the slower and less likely rumors about COVID-19 spread. This consequence tells us that the government needs to guide the public to the truth. Announcing the true information publicly could instantly contain the COVID-19 rumor diffusion well rather than making them hidden or voiceless.

#RumorsCOVID-19: Predicting the Forwarding of Online Rumors in Wuhan, China and in Israel

COVID-19 ushered in almost unprecedented socioeconomic and political challenges. A typical social reaction during such emergencies is rumormongering, which has intensified since the advent of social media. This study explored factors affecting users’ willingness to spread pandemic-related rumors in Wuhan, China and Israel. We tested a multi-variant model of factors affecting the forwarding of COVID-19 rumors. In an online survey conducted in April–May 2020, users of each country's leading social media platform (WeChat and WhatsApp, respectively) reported on patterns of exposure to and spread of COVID-19 rumors, as well as on their motives for doing so. Despite major differences between the two societies, interesting similarities were found: in both cases, individual drives, shaped by personal needs and degree of negative feelings, were the leading factors behind rumormongering. Exposure to additional sources of information regarding the rumors was also a significant predictor, but only in the Chinese case.

Rumor propagation dynamics in social networks under the influence of time delay and diffusion

Rumors in social networks are often referred to as infectious diseases of the Internet, because rumors spreading in networks feature strong concealment, fast transmission speed and wide spread. With the development of mobile devices, online rumors nowadays are far more harmful than before. Rumors in social networks show completely different spatiotemporal dynamics from traditional rumor spreading dynamics. A social network rumor spreading model with considering both reaction diffusion and fermentation time delay is proposed in this paper. The effects of spatial diffusion and time delay on rumor spreading in online social networks are studied. Firstly, the existence of equilibrium point of the reaction-diffusion rumor spreading model is analyzed, and the basic regeneration number <inline-formula><tex-math id="M2">\begin{document}$R_{0}$\end{document}</tex-math><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="18-20220726_M2.jpg"/><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="18-20220726_M2.png"/></alternatives></inline-formula> is calculated. When <inline-formula><tex-math id="M3">\begin{document}$R_{0} < 1$\end{document}</tex-math><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="18-20220726_M3.jpg"/><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="18-20220726_M3.png"/></alternatives></inline-formula>, the rumor stops spreading and disappears in social networks; when <inline-formula><tex-math id="M4">\begin{document}$R_{0}>1$\end{document}</tex-math><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="18-20220726_M4.jpg"/><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="18-20220726_M4.png"/></alternatives></inline-formula>, the rumor persists in social networks. Secondly, the local stability of the rumor spreading equilibrium is investigated by using the Roth-Hurwitz stability criterion, and the influence of diffusion on the system stability is discussed. When the diffusion is introduced into a stable rumor spreading model without time delay, the model becomes unstable, indicating that the Turing instability is caused by diffusion. Thirdly, the Hopf bifurcation condition of the rumor spreading model is established by selecting the time delay <i>τ</i> as the bifurcation parameter, and the expression of bifurcation threshold <inline-formula><tex-math id="M5">\begin{document}$\tau_{0}$\end{document}</tex-math><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="18-20220726_M5.jpg"/><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="18-20220726_M5.png"/></alternatives></inline-formula> is given. When <inline-formula><tex-math id="M6">\begin{document}$\tau < \tau_{0}$\end{document}</tex-math><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="18-20220726_M6.jpg"/><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="18-20220726_M6.png"/></alternatives></inline-formula>, the rumor propagation model with diffusion term is stable; when <inline-formula><tex-math id="M7">\begin{document}$\tau>\tau_{0}$\end{document}</tex-math><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="18-20220726_M7.jpg"/><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="18-20220726_M7.png"/></alternatives></inline-formula>, the model loses the stability and the Hopf bifurcation occurs. The numerical simulation results show that both diffusion and time delay play an important role in the dynamic evolution of rumor spreading. At the same time, the influence of the crowding degree of spreaders on rumor propagation is also simulated. As the crowding gets worse and worse, the rumor refuting effect weakens, the bifurcation threshold <inline-formula><tex-math id="M8">\begin{document}$\tau_{0}$\end{document}</tex-math><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="18-20220726_M8.jpg"/><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="18-20220726_M8.png"/></alternatives></inline-formula> decreases, and the propagation peak increases. Therefore, it is important to build an excellent social network environment to supervise the rumors that are still in the fermentation stage, improve the timeliness of the release of rumor refuting information, and strengthen the refuting of rumors among key groups. This paper breaks through the limitation considering only the time evolution, explores the spatiotemporal spreading law of rumor in real society, and provides a new perspective and idea for governing the rumor spreading.

Exploring S-shape curves and heterogeneity effects of rumor spreading in online collective actions.

Nowadays online collective actions are pervasive, such as the rumor spreading on the Internet. The observed curves take on the S-shape, and we focus on evolutionary dynamics for S- shape curves of online rumor spreading. For agents, key factors, such as internal aspects, external aspects, and hearing frequency jointly determine whether to spread it. Agent-based modeling is applied to capture micro-level mechanism of this S-shape curve. We have three findings: (a) Standard S-shape curves of spreading can be obtained if each agent has the zero threshold; (b) Under zero-mean thresholds, as heterogeneity (SD) grows from zero, S-shape curves with longer right tails can be obtained. Generally speaking, stronger heterogeneity comes up with a longer duration; and (c) Under positive mean thresholds, the spreading curve is two-staged, with a linear stage (first) and nonlinear stage (second), but not standard S-shape curves either. From homogeneity to heterogeneity, the spreading S-shaped curves have longer right tail as the heterogeneity grows. For the spreading duration, stronger heterogeneity usually brings a shorter duration. The effects of heterogeneity on spreading curves depend on different situations. Under both zero and positive-mean thresholds, heterogeneity leads to S-shape curves. Hence, heterogeneity enhances the spreading with thresholds, but it may postpone the spreading process with homogeneous thresholds.

A new spreading model in the environment of epidemic-related online rumors

This paper takes COVID-19-related online rumors as the research object, and explores the law of spreading public opinion in social networks. The paper also conducts empirical research on the relationship between rumor spreading, user characteristics and subject interest differences, and analyzes the common influence of individual factors and social environment. In the process of public opinion dissemination, measures that can effectively regulate the dissemination of public opinion are proposed. Based on the susceptible-exposed-infected-recovered (SEIR) model, this paper analyzes the influence of individual differentiation characteristics, friend factors, and time-dependent decline on user status changes. The study found that the user’s environment can affect the spread and popularity of public opinion information, and prolong the survival time of public Controlling the propagation threshold and exit threshold of the platform helps to control the large-scale dissemination of online public opinion. The extinction of public opinion is affected by the decline of time and heat rather than certain probability.

Characteristics, dissemination features and suppression mechanisms of rumors related to nutrition for chronic disease prevention and control

Objective To explore the characteristics of involved illnesses, disseminators, communication routes, and victims of rumors about nutrition and nutients intakes related to chronic diseases prevention and control and to provide policy and strategy recommendations for establishing rumor suppression mechanism. Methods With online searching in China National Knowledge Infrastructure, Wanfang Data, and National Newspaper and Magazines Index Database, we retrieved relevant literatures, reports and articles published between January 1, 2015 and November 31, 2019. Expert interviews and consultations were also conducted among 18 senior professionals in various relevant fields during September to December 2019. Results In all the disseminated nutrition rumors, the most involved chronic disease was cancer (being remarked in 25.13% of the rumors). Of the nutrition rumors, 40.91% were disseminated by means of self-media. Based on the estimation made by 55.56% (10/18) of senior professionals consulted, the ratio of online versus offline dissemination of the nutrition rumors was 8 : 2, indicating online dissemination as a major transmission way of the rumors. The majority (66.67%) of the victims of the disseminated nutrition rumors were the elderly people (38.9%) and chronic disease patients (27.8%). Conclusion The rumors about nutrition and nutients intakes related to chronic diseases prevention and control were mainly disseminated by online media and the potential adverse impact of the rumor is huge. Therefore, online rumor suppression and a long-term mechanism for cooperation among multiple social organizations in the rumor suppression should be promoted.

Emotions in online rumor diffusion

Emotions are regarded as a dominant driver of human behavior, and yet their role in online rumor diffusion is largely unexplored. In this study, we empirically study the extent to which emotions explain the diffusion of online rumors. We analyze a large-scale sample of 107,014 online rumors from Twitter, as well as their cascades. For each rumor, the embedded emotions were measured based on eight so-called basic emotions from Plutchik’s wheel of emotions (i.e., anticipation–surprise, anger–fear, trust–disgust, joy–sadness). We then estimated using a generalized linear regression model how emotions are associated with the spread of online rumors in terms of (1) cascade size, (2) cascade lifetime, and (3) structural virality. Our results suggest that rumors conveying anticipation, anger, and trust generate more reshares, spread over longer time horizons, and become more viral. In contrast, a smaller size, lifetime, and virality is found for surprise, fear, and disgust. We further study how the presence of 24 dyadic emotional interactions (i.e., feelings composed of two emotions) is associated with diffusion dynamics. Here, we find that rumors cascades with high degrees of aggressiveness are larger in size, longer-lived, and more viral. Altogether, emotions embedded in online rumors are important determinants of the spreading dynamics.

The evolution and governance of online rumors during the public health emergency: taking COVID-19 pandemic related rumors as an example

ABSTRACT The outbreak of the infodemic during COVID-19 caused mass panic in society. Studying the evolution law of online rumors in the relatively complete cycle of COVID-19 can improve the pertinence of rumor governance. In this paper, the Python crawler program was used to collect rumor-refuting microblogs. Based on the development of public opinion and the pandemic, it was divided into five stages, including incubation stage, explosion stage, digestion stage, fluctuation stage, and re-digestion stage. Then, the statistical analysis methods ranging from correlation analysis to chi-square analysis and analytical methods like hot trend analysis, stage-based analyses of quantity, hot words and subjects were used to study the dynamic evolution laws of online rumors from the perspective of quantity and content. The research found that online rumors had the rules of periodic evolution of quantity and periodic fluctuation of hot words and subjects, which were in line with the COVID-19 pandemic. Social platforms such as WeChat and Tik Tok were the main places for rumors’ generation and propagation. In different stages of rumor transmission, the public mood was staggered repeatedly, and the homogeneous or same rumors would spread repeatedly. Based on the above laws, the corresponding governance strategies were put forward.

Islamophobia Discourse via Online Rumors in Korea: Focusing on the Rumor “How Lebanon, which was a Christian Country, became an Islamic Country?” and the “Taharrush Game”

This paper aims to explore the current status of the phenomena of online Islamophobia in Korea and how hate rumours affect internet users. The paper analyses Islamophobic information that flows online in Korean society with two particular rumors as examples, “Taharrush Game” and “How Lebanon, which was a Christian Country, became an Islamic Country?” To identify Islamophobic fake news in Korea, the study reviewed previous cases of fake news in Korea and examined the processes of creation and dissemination of Islamophobic fake news through a review of the literature. Moreover, using the survey method and examining online postings, this paper analyzed the current situation of Islamophobic disinformation in South Korea.

Roles of Temporal Message Framing and Digital Channel Type in Perception and Dissemination of Food Risk Rumors

Now that online media channels have become important sources of risk information, online rumors about risks have become increasingly problematic. Guided by construal level theory and the social-mediated crisis communication model, this study tests direct, mediating, and moderating effects of temporal message frame and digital media channel type on people’s perceptions of food risk rumors and their intentions to share them. An online experiment with a 2 temporal frame (near vs. distant in time) x 2 channel type (web portal vs. social media site) between-subjects design was conducted among 413 Korean adults. Results show that risk perceptions are affected more by the channel on which rumor information is encountered than by the framing of the information. Specifically, rumor messages presumed to appear on social media generated (a) higher perceived susceptibility than those presumed to appear on web portals (main effects) and (b) higher levels of perceived susceptibility in a distant-future frame condition than in a near-future frame condition (conditional moderating effects). Perceived susceptibility also mediated the interaction effects of temporal frame and channel type on intention to share rumor. This study provides theoretical and practical implications for digital media channel effects on risk perceptions and dissemination intention for risk rumors.

A rumor reversal model of online health information during the Covid-19 epidemic

The development of the Internet and social media has expanded the speed and scope of information dissemination, but not all widely disseminated information is true. Especially during the public health emergencies, the endogenous health information demand generated by the lack of scientific knowledge of health information among online users stimulates the dissemination of health information by mass media while providing opportunities for rumor mongers to publish and spread online rumors. Invalid scientific knowledge and rumors will have a serious negative impact and disrupt social order during epidemic outbreaks such as COVID-19. Therefore, it is extremely important to construct an effective online rumor reversal model. The purpose of this study is to build an online rumor reversal model to control the spread of online rumors and reduce their negative impact. From the perspective of internal and external factors, based on the SIR model, this study constructed a G-SCNDR online rumor reversal model by adopting scientific knowledge level theory and an external online rumor control strategy. In this study, the G-SCNDR model is simulated, and a sensitivity analysis of the important parameters of the model is performed. The reversal efficiency of the G-SCNDR model can be improved by properly adopting the isolation-conversion strategy as the external control approach to online rumors with improving the popularization rate of the level of users' scientific knowledge and accelerating the transformation efficiency of official nodes. This study can help provide a better understanding of the process of online rumor spreading and reversing, as well as offering ceritain guidance and countermeasures for online rumor control during public health emergencies.