•We build new double-rumors concurrently spreading models.•Without rumors priorities, we introduce a selection parameter for spreaders to express the attractions of different rumors.•We introduce ...states-vector to describe rumors states of each node, provide the double-rumors dissemination mechanism by states-vectors expressions.•Simulation results indicate that the best start time of new rumor exists explicitly for two rumors spread process.•Large coreness nodes are shown to be the relative better promulgators for the new rumor.
For there are always several kinds of rumors spreading simultaneously in real networks, the research about multiple rumors propagation process is necessary and significant. In this paper, considering the spread of two rumors with different launch time, and assuming the content of each rumor may have nothing to do with the others, we study the double-rumors concurrently spreading dynamics in complex networks, and introduce two kinds of double-rumors spreading models: the DSIR model and the C-DSIR model. We then provide the double-rumors dissemination mechanism by states-vectors expressions and derive the mean-field equations of models to describe their dynamics. Particularly, without rumors priorities, we introduce a selection parameter θ for spreaders to express the attractions of different rumors, and study the influence of this parameter on double-rumors spreading. Numerical simulations are performed to explore the interaction between two rumors, and we investigate the spreading peak and the final size of the rumors with various parameters. Simulation results indicate that, the best launch time of new rumor exists explicitly for the DSIR model, the selection parameter θ and the delay time Tin are interdependent quantities, and the closer the start time of new rumor is to the best time, the more obvious the interdependence would be. Meanwhile, Tin is also a network-dependent parameter for our models in a series of BA networks. Furthermore, under the same conditions, the influential nodes identified by large coreness are the relative better promulgators for new rumor, so they are what the strategy should give priorities to. Our experiment reveals some interesting patterns of double-rumors spreading and suggest a possible avenue for further study of interplays of multiple pieces of information in complex network.
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.
Current studies have considered the upper growth limit of the information quantity of online public opinion, although the effect of online rumors on the upper growth limit has not been considered. ...This study aims to identify the key parameters in a model of online rumors that affect the upper growth limit. First, the logistic population growth model is introduced to analyze the mechanism underlying the impact of online rumors on the information quantity of online public opinion. Second, the theory of differential equations is employed to build an influence rule between the two models. Third, we perform a numerical simulation to explore the development trend of the information quantity of online public opinion under the control of three parameters: rumor input rate, rumor conversion rate and rumor refutation rate. This paper defined the key factors for assessing how online public opinions are affected by online rumors, determined the influence strength of parameters under different online public opinion modes, better described the abnormal growth pattern of online public opinion, and provided a theoretical basis for online public opinion prediction and rumor control research.
•The rumor input rate, rumor conversion rate and rumor refutation rate are the key factors for assessing how online public opinions are affected by online rumors.•The rumor conversion rate presents an impact in all scenarios, especially sleepy scenarios.•The effect of controlling the rumor refutation rate is limited.•Controlling the rumor conversion rate is an effective method of controlling rumors.
Purpose/Significance As a new means of information dissemination, short videos have become a new favorite of some people in spreading rumors and refuting rumors due to their characteristics of ...visibility, convenience, and freedom of expression. It is of great significance to understand the content characteristics of health short videos in rumor refuting and improve their spreading effect. Method/Process This paper uses Python to conduct data mining, crawling the rumor refuting short videos related to the theme of COVID-19 epidemic prevention and control as samples, and the data set obtained includes the published articles and the original data, such as the number of forwards, and comments. Based on "logos", "ethos" and "pathos" in Aristotle's rhetoric theory, this paper codes the persuasion strategies of sample videos in combination with the coding standard table of 13 persuasion strategies under four categories. At the same time, it divides short videos into seven video elements under two categories and
Fake Cures Ghenai, Amira; Mejova, Yelena
Proceedings of the ACM on human-computer interaction,
11/2018, Volume:
2, Issue:
CSCW
Journal Article
Peer reviewed
Social media's unfettered access has made it an important venue for health discussion and a resource for patients and their loved ones. However, the quality of information available, as well as the ...motivations of its posters, has been questioned. This work examines the individuals on social media that are posting questionable health-related information, and in particular promoting cancer treatments which have been shown to be ineffective (making it a kind of misinformation, willful or not). Using a multi-stage user selection process, we study 4,212 Twitter users who have posted about one of 139 such "treatments", and compare them to a baseline of users generally interested in cancer. Considering features capturing user attributes, writing style, and sentiment, we build a classifier which is able to identify users prone to propagate such misinformation at an accuracy of over 90%, providing a potential tool for public health officials to identify such individuals for preventive intervention.
Brand rumors can harm brands' image and bring significant impacts on customers' decision-making and sharing behavior. Finding practical strategies for preventing the spread of brand rumors continues ...to be a challenge. Building on the social contagion theory, the current research enriches the discussion on understanding why people spread rumors and how to deal with the spreading of rumors. Sharing brand rumors is motivated by a variety of complex psychological reasons, but prior research didn't adequately analyze the problem from a complexity perspective. Therefore, using a sample of 416 interviewers within eight types of brand rumors, this study employs fuzzy-set qualitative comparative analysis (fsQCA) to investigate the combination of rumor psychological communication motivations in brand activities and solutions to prevent the spread of brand rumors. The current study discoveries three and two first-level configurational solutions, respectively, that can promote positive and negative rumor spreading. To summarize, emotional stimulation is a key component in the spread of rumors; altruism and relationship management motivation can coexist at times; and untrusted rumors are disseminated through other motivation factors. Solutions to prevent rumors from spreading are also provided. Furthermore, the findings help to understand the psychology of configurational motivation and how it can help brands reduce the spread of brand rumors. Finally, these discoveries' theoretical contributions and practical implications are presented.
Widely spread health-related rumors may mislead the public, escalate social panic, compromise government credibility, and threaten public health. Social collaboration models that maximize the ...functions and advantages of various agents of socialization can be a promising way to control health-related rumors. Existing research on health-related rumors, however, is limited in studying how various agents collaborate with each other to debunk rumors. This study utilizes content analysis to code the text data of health-related rumor cases in China during the COVID-19 pandemic. The study found that socialized rumor-debunking models could be divided into the following five categories: the government-led model, the media-led model, the scientific community-led model, the rumor-debunking platform-led model, and the multi-agent collaborative model. In addition, since rumors in public health crises often involve different objects, rumor refutation requires various information sources; therefore, different rumor-debunking models apply. This study verifies the value of socialized collaborative rumor debunking, advocates and encourages the participation of multiple agents of socialization and provides guidance for establishing a collaborative rumor-debunking model, thereby promoting efficient rumor-debunking methods and improving the healthcare of society.
This paper reports the findings of a 606-participant study analyzing the perception of, and engagement with, COVID-19 vaccine rumors on efficacy and mass immunization effort on Twitter. ...Misperceptions were successfully induced through simple content alterations and the addition of popular anti-COVID-19 hashtags such as #COVIDIOT and #covidhoax to otherwise valid Twitter content. Twitter's soft moderation warning label helped the majority of our participants to dismiss the rumors about mass immunization. However, for the skeptic, vaccine-hesitant minority, the soft moderation caused a “backfire effect” i.e., make them perceive the rumor as accurate. While the majority of the participants staunchly refrain from engaging with the COVID-19 rumors, the hesitant and skeptic minority was open to comment, retweet, like and share the vaccine efficacy rumors. Based on these findings, we recommend misinformation label designs to prevent the “backfire effect” of COVID-19 vaccine rumors on Twitter.
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