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When the spread of online health rumors on social media causes public concerns, the public is calling for action. However, little study has investigated how Facebook reaction icons (expressing feelings function) affect online users' behavioral intentions (intention to trust and share) toward online health rumor posts. The current study addresses this gap by focusing on the effect of Facebook reaction icons in two conditions: Facebook reaction icons' presence (versus absence), and Facebook reaction icons' emotional valence (positive versus negative versus neutral). Moreover, the authors also investigated the interaction between Facebook reaction icons' emotional valence and online health rumor posts' framing headlines (gain versus loss).

The authors used a 7 (Facebook reaction icons: Love, Like, Haha, Wow, Sad, Angry and no icon) × 2 (Facebook framing headlines: gain and loss) between-subjects design, analyzing 507 samples from online users with one-way ANOVA and MANOVA.

Results show that online health rumor posts without Facebook reaction icons are more likely to negatively change online users' behavioral intentions than the posts with Facebook reaction icons; negative reaction icons (Sad and Angry) lower online users' behavioral intentions than positive reaction icons (Love and Like). Further, the incongruency effect of interaction (i.e. positive reaction icons with a negative message) would have more negative effects on online users' behavioral intentions than the congruency effect (i.e. positive reaction icons with a positive message).

This study has rich contributions to theoretical and practical implications for the Facebook platform and Facebook users to apply Facebook reaction icons against online health rumor posts.

Dealing with online rumors or fake information on social media is growing in importance. Most academic research on online rumors has approached the issue from a quantitative modeling perspective. Less attention has been paid to the psychological mechanisms accounting for online rumor transmission behavior on the individual level. Drawing from the theory of stimulus–organism–response, this study aims to explore the nature of online rumors and investigate how the informational characteristics of online rumors are processed through the mediation of psychological variables to promote online rumor forwarding.

An experimental approach to this issue was taken; the researchers investigated how the informational characteristics of online rumors and the psychological mediators promote online rumor transmission.

Four information characteristics (sense-making, funniness, dreadfulness and personal relevance) and three psychological motivators (fact-finding, relationship enhancement and self-enhancement) promote online rumor-forwarding behavior.

Because any online rumor transmitted on social media can go viral, companies may eventually encounter social media-driven crises. Thus, understanding what drives rumor-forwarding behavior can help marketers mitigate and counter online rumors.

The Internet is a breeding ground for rumors. A way to tackle the problem involves the use of counter-rumor messages that refute rumors. This paper analyzes users' intention to follow rumors and counter-rumors as a function of two factors: individuals' risk propensity and messages' prior endorsement.

The paper conducted an online experiment. Complete responses from 134 participants were analyzed statistically.

Risk-seeking users were keener to follow counter-rumors compared with risk-averse ones. No difference was detected in terms of their intention to follow rumors. Users' intention to follow rumors always exceeded their intention to follow counter-rumors regardless of whether prior endorsement was low or high.

This paper contributes to the scholarly understanding of people's behavioral responses when, unknowingly, exposed to rumors and counter-rumors on the Internet. Moreover, it dovetails the literature by examining how risk-averse and risk-seeking individuals differ in terms of intention to follow rumors and counter-rumors. It also shows how prior endorsement of such messages drives their likelihood to be followed.

The paper explores the hitherto elusive question: When users are unknowingly exposed to both a rumor and its counter-rumor, which entry is likely to be followed more than the other? It also takes into consideration the roles played by individuals' risk propensity and messages' prior endorsement.

Negative rumors damage the destination’s image and tourist experience. This study aims to compare how rumor correction sources (government vs business vs tourist) affect user online citizenship behavior (UOCB).

Based on the stimuli-organism-response framework, a hypothetical model was established from rumor correction to UOCB. Three scenario experiments (more than 1,000 valid samples) were designed. Study 1 illustrated the effects of different rumor corrections, Study 2 was designed to verify the mediating effects of sympathy and perceived information authenticity (PIA) and the robustness of results was demonstrated in Study 3.

Government correction elicited the highest sympathy and PIA. Business correction was less than tourist correction in arousing sympathy but better than tourist correction in enhancing PIA. Sympathy and PIA had a mediating effect on the relationship between rumor correction and UOCB.

This study helps to identify the different advantages of rumor correctors and provides insights to prevent the deterioration of negative tourism rumors or even reverse these crises.

This study innovates research perspective of negative tourism rumor governance, expands the understanding of the effect and process of rumor correction and enriches the research content of tourism crisis communication.

负面谣言破坏目的地形象和游客体验。本研究比较谣言纠正来源（政府、企业、游客）对用户在线公民行为的影响。

基于刺激-有机体-反应框架, 搭建谣言纠正到用户在线公民行为的假设模型, 并设计3个情境实验（超过1000个有效样本）。实验1验证不同谣言纠正来源的纠正效果, 实验2证明同情和感知信息真实性的中介作用, 实验3测试实验结果的稳健性。

政府纠正引发最高的同情和感知信息真实性。企业纠正在唤起同情时不足于游客纠正, 但在增强感知信息真实性时优于旅游纠正。同情和感知信息真实性在谣言纠正与用户在线公民行为之间发挥中介作用。

有助于识别各个谣言纠正主体的不同优势, 为防止旅游负面谣言恶化甚至转危为安提供见解。

为旅游负面谣言治理提供新的研究视角, 拓展了对谣言纠正效果和过程的认识, 丰富了旅游危机沟通的研究内容。

Los rumores negativos dañan la imagen del destino y la experiencia del turista. Este estudio compara cómo afectan las fuentes de corrección de rumores (gobierno vs empresas vs turista) en el comportamiento cívico online de los usuarios (CCOU).

Sobre la base del marco estímulo-organismo-respuesta, se estableció un modelo hipotético desde la corrección de rumores hasta el CCOU. Se diseñaron tres escenarios experimentales (más de 1.000 muestras válidas). El Estudio 1 ilustró los efectos de las diferentes correcciones de rumores, el Estudio 2 se diseñó para verificar los efectos mediadores de la simpatía y la autenticidad percibida de la información (API), y la solidez de los resultados se demostró en el Estudio 3.

La corrección del gobierno obtuvo la mayor simpatía y API. La corrección de la empresa despertó menos simpatía que la corrección del turista, pero fue mejor para generar API. La simpatía y la API tuvieron un efecto mediador en la relación entre la corrección del rumor y el CCOU.

Ayuda a identificar las diferentes ventajas de los correctores de rumores y proporciona información para prevenir el deterioro de los rumores turísticos negativos o incluso revertir estas crisis.

Proporciona una nueva perspectiva de investigación de la gobernanza del rumor turístico negativo, amplía la comprensión del efecto y el proceso de corrección de rumores y enriquece el contenido de la investigación de la comunicación de crisis turísticas.

The purpose of this paper is to achieve effective governance of online rumors through the proposed rumor propagation model and immunization strategy.

The paper leverages the agent-based modeling (ABM) method to model individuals from two aspects, behavior and attitude. Based on the analysis and research of online data, we propose a rumor propagation model, namely the Untouched view transmit removed-Susceptible hesitate agree disagree (Unite-Shad), and devise an immunization strategy, namely the Gravity Immunization Strategy (GIS). A graph-based framework, namely Pregel, is used to carry out the rumor propagation simulation experiments. Through the experiments, the rationality of the Unite-Shad and the effectiveness of the GIS are verified.

The study discovers that the inconsistency between human behaviors and attitudes in rumor propagation can be explained by the Unite-shad model. Besides, the GIS, which shows better performance in small-world networks than in scale-free networks, can effectively suppress rumor propagation in the early stage.

This paper provides an effective immunization strategy for rumor governance. Specifically, the Unite-Shad model reveals the mechanism of rumor propagation, and the GIS provides an effective governance method for selecting immune nodes.

The inconsistency of human behaviors and attitudes in real scenes is modeled in the Unite-Shad model. Combined with the model, the definition of diffusion domain is proposed and a novel immunization strategy, namely GIS, is designed, which is significant for the social governance of rumor propagation.

The purpose of the study is to understand how socially shared misinformation and rumors can enhance the motivation to protect personal interests and enhance social practices of panic buying.

The study employed a number of qualitative data collection methods for the purpose of triangulation, as it can offer thick interpretation and can help to develop a context specific research framework.

The shared misinformation and rumors on social media developed into psychological, physical and social threats; therefore, people started panic buying to avoid these negative consequences. People believed that there were differences between the information shared by politicians and government officials and reality, such as “everything is under control,” whereas social media showed people standing in long queues and struggling to buy the necessities of life. The shared misinformation and rumors on social media became viral and received social validation, which created panic buying in many countries.

It is the responsibility of government, politicians, leaders, media and the public to control misinformation and rumors, as many people were unable to buy groceries due either to socio-economic status or their decisions of late buying, which increased depression among people.

The study merged the theory of rumor (TORT) transmission and protection motivation theory (PMT) to understand how misinformation and rumors shared through social media increased global uncertainty and the desire to panic buy across the world.

This paper aims to investigate the impacts of rumors' information characteristics on people's believing and spreading of rumors online.

This study employed a mixed-methods approach by combining qualitative and quantitative methods. In study 1, the authors explored different types of rumors and their information source characteristics through qualitative research. In study 2, the authors utilized the findings from study 1 to develop an empirical model to verify the impact of these characteristics on the public's behaviors of believing and spreading rumors by content analysis and quantitative research.

The results show that five information source characteristics – credibility, professionalism, attractiveness, mystery and concreteness – influence the spreading effect of different types of rumors.

This study contributes to rumor spreading research by deepening the theory of information source characteristics and adding to the emerging literature on the COVID-19 pandemic.

Insights from this research offer important practical implications for policymakers and online-platform operators by highlighting how to suppress the spread of rumors, particularly those associated with COVID-19.

This research introduces the theory of information source characteristics into the field of rumor spreading and adopts a mixed-methods approach, taking COVID-19 rumors as a typical case, which provides a unique perspective for a deeper understanding of rumor spreading's antecedences.

Purpose: The main purpose of the study is to understand the factors that facilitate correction behavior among individuals. In this study the authors examine the impact of self-perceived media literacy (SPML) and reflection on participants’ correction behavior.

Methods: Data for the study were collected from Amazon's MTurk using an online survey. Data were collected after a certificate of exemption was received by the Institutional Review Board in a research university in the United States (US) Qualtrics software was used to collect data. The total number of participants was 797.

Findings: The findings show that although both SPML and reflection are positively associated with rumor refutation, higher SPML alone is not enough. Reflective judgment is critical for individuals to take part in this behavior online, such that individuals with higher reflective judgment indicated that they refute rumors online, irrespective of their SPML score.

Originality: The authors tested the relationship of multiple variables with participants correction behavior. Although research shows the importance of social correction, there is not much knowledge about what facilitates actual misinformation correction.

In the wake of a rumor outbreak, individuals exchange three types of messages: rumor messages, counter-rumor messages, and uncertainty-expressing messages. However, the properties of the three types of messages are relatively unknown particularly in the social media context. Hence, the purpose of this paper is to examine these three types of messages posted on social media in the wake of a rumor outbreak.

Data included tweets posted after the outbreak of a rumor that wrongly accused the fast food chain Kentucky Fried Chicken (KFC) for selling rats instead of chicken. Using a deductive approach, codes were derived via content analysis on the tweets. Volume and exposure of tweets were also examined.

Counter-rumor tweets (52 percent) outnumbered rumors tweets (32 percent) and uncertainty-expressing tweets (16 percent). Emotions and personal involvement were abundant in rumor tweets. Expressions of credence and references to URLs were high in counter-rumor tweets. Social ties were found widely in uncertainty-expressing tweets. The high volume and exposure of counter-rumor tweets compared with those of either rumor tweets or uncertainty-expressing tweets highlight the potential of counter-rumors to mitigate rumors.

This research ventures into a relatively unexplored territory by concurrently examining rumor messages, counter-rumor messages and uncertainty-expressing messages in the wake of a rumor outbreak. It reveals that counter-rumor messages have the potential to mitigate rumors on social media.

With the rapid development of internet technology, open online social networks provide a broader platform for information spreading. While dissemination of information provides convenience for life, it also brings many problems such as security risks and public opinion orientation. Various negative, malicious and false information spread across regions, which seriously affect social harmony and national security. Therefore, this paper aims to minimize negative information such as online rumors that has attracted extensive attention. The most existing algorithms for blocking rumors have prevented the spread of rumors to some extent, but these algorithms are designed based on entire social networks, mainly focusing on the microstructure of the network, i.e. the pairwise relationship or similarity between nodes. The blocking effect of these algorithms may be unsatisfactory in some networks because of the sparse data in the microstructure.

An algorithm for minimizing the influence of dynamic rumor based on community structure is proposed in this paper. The algorithm first divides the network into communities, and integrates the influence of each node within communities and rumor influence probability to measure the influence of each node in the entire network, and then selects key nodes and bridge nodes in communities as blocked nodes. After that, a dynamic blocking strategy is adopted to improve the blocking effect of rumors.

Community structure is one of the most prominent features of networks. It reveals the organizational structure and functional components of a network from a mesoscopic level. The utilization of community structure can provide effective and rich information to solve the problem of data sparsity in the microstructure, thus effectively improve the blocking effect. Extensive experiments on two real-world data sets have validated that the proposed algorithm has superior performance than the baseline algorithms.

As an important research direction of social network analysis, rumor minimization has a profound effect on the harmony and stability of society and the development of social media. However, because the rumor spread has the characteristics of multiple propagation paths, fast propagation speed, wide propagation area and time-varying, it is a huge challenge to improve the effectiveness of the rumor blocking algorithm.