Journal articles: 'Rutor'

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Monticelli, Damiano, Constant M. G. van den Berg, Andrea Pozzi, and Carlo Dossi. "Copper Speciation in Glacial Stream Waters of Rutor Glacier (Aosta Valley, Italy)." Australian Journal of Chemistry 57, no. 10 (2004): 945. http://dx.doi.org/10.1071/ch04181.

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The chemical speciation of copper in stream waters from Rutor Glacier was determined by cathodic stripping voltammetry with ligand competition against salicylaldoxime. The complexation of salicylaldoxime was calibrated at various calcium concentrations, the major competing cation in these waters. Copper concentrations (3–7 nM) were approximately ten-fold lower than typical for rain waters in this region, indicating that copper had been removed by adsorption onto rock and other particles. Strong copper binding ligands, with log K′CuL = 12.5–12.9, were detected in all samples, including waters emerging from beneath the glacier, with no detectable change in the ligand composition down stream. The results suggest that the ligands could originate from in situ production from algae in snow and ice, or directly from the precipitation.

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Burga, C. A. "Végétation et paléoclimatologie de l'Holocène moyen d'une ancienne tourbière située au front du Glacier du Rutor, 2 510m (Vallée d'Aoste, Italie). / Vegetation and paleoclimatology of the Middle Holocene of a former peat bog situated at the front of the Rutor Glacier, 2510 m (Aosta valley, Italy)." Revue de géographie alpine 83, no. 1 (1995): 9–16. http://dx.doi.org/10.3406/rga.1995.3787.

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Badino, Federica, Cesare Ravazzi, Francesca Vallè, Roberta Pini, Amelia Aceti, Michele Brunetti, Elena Champvillair, et al. "8800 years of high-altitude vegetation and climate history at the Rutor Glacier forefield, Italian Alps. Evidence of middle Holocene timberline rise and glacier contraction." Quaternary Science Reviews 185 (April 2018): 41–68. http://dx.doi.org/10.1016/j.quascirev.2018.01.022.

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Burga, Conradin A. "Vegetation History and Palaeoclimatology of the Middle Holocene: Pollen Analysis of Alpine Peat Bog Sediments, Covered Formerly by the Rutor Glacier, 2510 m (Aosta Valley, Italy)." Global Ecology and Biogeography Letters 1, no. 5 (September 1991): 143. http://dx.doi.org/10.2307/2997428.

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Zhang, Yaming, Yanyuan Su, Weigang Li, and Haiou Liu. "Modeling rumor propagation and refutation with time effect in online social networks." International Journal of Modern Physics C 29, no. 08 (August 2018): 1850068. http://dx.doi.org/10.1142/s0129183118500687.

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Rumor propagation and refutation form an important issue for spreading dynamics in online social networks (OSNs). In this paper, we introduce a novel two-stage rumor propagation and refutation model with time effect for OSNs. The dynamical mechanism of rumor propagation and refutation with time effect is investigated deeply. Then a two-stage model and the corresponding mean-field equations in both homogeneous and heterogeneous networks are obtained. Monte Carlo simulations are conducted to characterize the dynamics of rumor propagation and refutation in both Watts–Strogatz network and Barabási–Albert network. The results show that heterogeneous networks yield the most effective rumor and anti-rumor spreading. Besides, the sooner authority releases anti-rumor and the more attractive anti-rumor is, the less rumor influence is. What’s more, these findings suggest that individuals’ ability to control themselves and identify rumor accurately should be improved to reduce negative impact of rumor effectively. The results are helpful to understand better the mechanism of rumor propagation and refutation in OSNs.

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BODAGHI, AMIRHOSEIN, and SAMA GOLIAEI. "A NOVEL MODEL FOR RUMOR SPREADING ON SOCIAL NETWORKS WITH CONSIDERING THE INFLUENCE OF DISSENTING OPINIONS." Advances in Complex Systems 21, no. 06n07 (September 2018): 1850011. http://dx.doi.org/10.1142/s021952591850011x.

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Rumor spreading is a good sample of spreading in which human beings are the main players in the spreading process. Therefore, in order to have a more realistic model of rumor spreading on online social networks, the influence of psycho-sociological factors particularly those which affect users’ reactions toward rumor/anti-rumor should be considered. To this aim, we present a new model that considers the influence of dissenting opinions on those users who have already believed in rumor/anti-rumor but have not spread the rumor/anti-rumor yet. We hypothesize that influence is a motive for the believers to spread their beliefs in rumor/anti-rumor. We derive the stochastic equations of the new model and evaluate it by using two real datasets of rumor spreading on Twitter. The evaluation results support the new hypothesis and show that the novel model which is relied on the new hypothesis is able to better represent rumor spreading.

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Sun, Ling, Yun Liu, Qing-An Zeng, and Fei Xiong. "A novel rumor diffusion model considering the effect of truth in online social media." International Journal of Modern Physics C 26, no. 07 (April 30, 2015): 1550080. http://dx.doi.org/10.1142/s0129183115500801.

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In this paper, we propose a model to investigate how truth affects rumor diffusion in online social media. Our model reveals a relation between rumor and truth — namely, when a rumor is diffusing, the truth about the rumor also diffuses with it. Two patterns of the agents used to identify rumor, self-identification and passive learning are taken into account. Combining theoretical proof and simulation analysis, we find that the threshold value of rumor diffusion is negatively correlated to the connectivity between nodes in the network and the probability β of agents knowing truth. Increasing β can reduce the maximum density of the rumor spreaders and slow down the generation speed of new rumor spreaders. On the other hand, we conclude that the best rumor diffusion strategy must balance the probability of forwarding rumor and the probability of agents losing interest in the rumor. High spread rate λ of rumor would lead to a surge in truth dissemination which will greatly limit the diffusion of rumor. Furthermore, in the case of unknown λ, increasing β can effectively reduce the maximum proportion of agents who do not know the truth, but cannot narrow the rumor diffusion range in a certain interval of β.

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Kushner, A. "Rumor." Literary Imagination 13, no. 3 (August 25, 2011): 320. http://dx.doi.org/10.1093/litimag/imr077.

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Pal, Anjan, Alton Y. K. Chua, and Dion Hoe-Lian Goh. "Does KFC sell rat? Analysis of tweets in the wake of a rumor outbreak." Aslib Journal of Information Management 69, no. 6 (November 20, 2017): 660–73. http://dx.doi.org/10.1108/ajim-01-2017-0026.

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Purpose 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. Design/methodology/approach 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. Findings 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. Originality/value 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.

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Ji, Peinan, Xiangbin Yan, and Guang Yu. "Can Rumor Clarification Eliminate the Effects of Rumors?" International Journal of Asian Business and Information Management 11, no. 1 (January 2020): 48–62. http://dx.doi.org/10.4018/ijabim.2020010103.

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This article analyzes the effects of rumor and official rumor clarification on Chinese stock returns under different rumor conditions using an event study. The results are based on a sample of 832 rumor clarification announcements from China Listed Companies spanning the period of 2015 to 2017. The results show that the average cumulative abnormal return after the rumor event is significantly positive in the positive rumor sample and neutral sample, and significantly negative in the negative rumor sample. After the clarification announcements, we find the announcements effective for the positive and neutral rumor sample, but not in the case of the negative sample. However, by comparing different clarification times of each sample, we find that the earlier the clarification time is, the smaller the impact on the companies in positive and negative rumor examples.

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Huo, Liang’an, and Yuqing Zhang. "Effect of Global and Local Refutation Mechanism on Rumor Propagation in Heterogeneous Network." Mathematics 10, no. 4 (February 14, 2022): 586. http://dx.doi.org/10.3390/math10040586.

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In the process of rumors propagation, the behavior of individuals to propagation or refutation is not only influenced by the surrounding global environment but also the local environment. In this paper, a modified rumor propagation model is proposed considering the global and local effects of the rumor refutation mechanism and the activity rate of individuals in a heterogeneous network, and the dynamics process of the rumor propagation is derived by using the mean-field equation. Combining theoretical proving and simulation analysis, it shows that the critical threshold of rumor propagation has a great relationship with individual activity rates and global and local effects of the rumor refutation mechanism. The greater the government’s efforts to refute rumors, the lower the critical threshold of rumor propagation and the smaller the final rumor size. While relatively, people are much more likely to believe the global rumor refutation information taken with official information, local rumor refutation information has little influence on rumor propagation.

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Ding, Qian, and Xingyu Luo. "People with High Perceived Infectability Are More Likely to Spread Rumors in the Context of COVID-19: A Behavioral Immune System Perspective." International Journal of Environmental Research and Public Health 20, no. 1 (December 30, 2022): 703. http://dx.doi.org/10.3390/ijerph20010703.

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Since the outbreak of COVID-19, many studies have explored the influencing factors of rumor spreading, such as anxiety, risk perception and information source credibility, but few studies have focused on the impact of individual differences. Based on the theory of behavioral immune systems, we investigated the impact of perceived infectability on rumor spreading and the mediating role of rumor trust in the context of COVID-19. Two studies were investigated using the scale and recall–report task of rumor spreading. The results show that perceived infectability was a significant positive predictor of rumor spreading. However, the impact of perceived infectability on rumor spreading was not direct, and it mainly indirectly affected rumor spreading through the mediating role of rumor trust. Overall, the findings suggest that individuals with high perceived infectability are more likely to believe rumors and then spread rumors during the epidemic. This study advances the literature on rumor spreading and behavioral immune systems and provides practical implications to anti-rumor campaigns.

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Du, Xinyu, Limei Ou, Ye Zhao, Qi Zhang, and Zongmin Li. "Applications of Advanced Analysis Technologies in Precise Governance of Social Media Rumors." Applied Sciences 11, no. 15 (July 22, 2021): 6726. http://dx.doi.org/10.3390/app11156726.

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Social media rumor precise governance is conducive to better coping with the difficulties of rumor monitoring within massive information and improving rumor governance effectiveness. This paper proposes a conceptual framework of social media rumor precise governance system based on literature mining. Accordingly, insightful directions for achieving social media rumor precise governance are introduced, which includes (1) rational understanding of social media rumors, especially large-scale spreading false rumors and recurring false rumors; (2) clear classification of rumor spreaders/believers/refuters/unbelievers; (3) scientific evaluation of rumor governance effectiveness and capabilities. For the above three directions, advanced analysis technologies applications are then summarized. This paper is beneficial to clarify and promote the promising thought of social media rumor precise governance and create impacts on the technologies’ applications in this area.

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Wang, Yan, Feng Qing, Jian-Ping Chai, and Ye-Peng Ni. "Spreading Dynamics of a 2SIH2R, Rumor Spreading Model in the Homogeneous Network." Complexity 2021 (February 10, 2021): 1–9. http://dx.doi.org/10.1155/2021/6693334.

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With the rapid development of social network in recent years, the threshold of information dissemination has become lower. Most of the time, rumors, as a special kind of information, are harmful to society. And once the rumor appears, the truth will follow. Considering that the rumor and truth compete with each other like light and darkness in reality, in this paper, we study a rumor spreading model in the homogeneous network called 2SIH2R, in which there are both spreader1 (people who spread the rumor) and spreader2 (people who spread the truth). In this model, we introduced discernible mechanism and confrontation mechanism to quantify the level of people's cognitive abilities and the competition between the rumor and truth. By mean-field equations, steady-state analysis, and numerical simulations in a generated network which is closed and homogeneous, some significant results can be given: the higher the discernible rate of the rumor, the smaller the influence of the rumor; the stronger the confrontation degree of the rumor, the smaller the influence of the rumor; the larger the average degree of the network, the greater the influence of the rumor but the shorter the duration. The model and simulation results provide a quantitative reference for revealing and controlling the spread of the rumor.

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Huo, Liang’an, Sijing Chen, Xiaoxiao Xie, Huiyuan Liu, and Jianjia He. "Optimal Control of ISTR Rumor Propagation Model with Social Reinforcement in Heterogeneous Network." Complexity 2021 (December 22, 2021): 1–15. http://dx.doi.org/10.1155/2021/5682543.

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The wide spread of rumor is undoubtedly harmful to social stability; we should try to lower the effect of rumor on society. Therefore, it is reasonable to put forward the rumor control strategy on the basis of the study of the law of rumor propagation. Firstly, the ISTR model of rumor is established by including influencing factors of true information spreader and social reinforcement. And by using the next generation matrix method, the basic reproduction number of rumor is obtained. Then, in order to minimize the adverse effects of rumors, through introducing two control strategies of scientific knowledge popularization and refutation of rumors, the optimal control problem is established. And through using Pontryagin’s Minimum Principle, the optimal solution of the rumor propagation model is solved. Finally, through theoretical analysis and numerical simulation, some results can be obtained. The results show that adding true information spreaders into the rumor model can effectively control the rumor propagation, and social reinforcement plays a significance role in rumor. The results also prove that these two control strategies can effectively inhibit the propagation of rumors. With the addition of control strategies, the number of true information spreaders increases, while the number of rumor spreaders decreases.

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Chen, Jianhong, Hongcai Ma, and Shan Yang. "SEIOR Rumor Propagation Model Considering Hesitating Mechanism and Different Rumor-Refuting Ways in Complex Networks." Mathematics 11, no. 2 (January 5, 2023): 283. http://dx.doi.org/10.3390/math11020283.

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Considering that the state transfer rules between nodes in existing rumor propagation models are mostly based on a single propagation mechanism, and most of the models have a single way of refuting rumors, in this paper, a new SEIOR rumor propagation model (ignorant (S), hesitators (E), spreaders (I), rumor debunkers (O), immunizers (R)) is proposed by introducing hesitators and rumor debunkers and combining different rumor-refuting ways of rumor debunkers. Firstly, the dynamics process of the propagation model is described by using the mean-field equations. Secondly, the equilibrium point and the basic regeneration number of the model are solved, and the existence and stability of the equilibrium point are discussed. Then, numerical simulations are used to analyze the effects of different factors on rumor propagation patterns. The results show that the rumor-spreading rate α2 has the greatest effect on rumor propagation. With the increase in α2, the degree of influence of the hesitator-converting rate α1 on the scale of rumor propagation first increases and then decreases. Different rumor-refuting ways have different inhibiting effects on the spread of rumors. Finally, based on the results of the theoretical proving and numerical analysis, some targeted measures to control the spread of rumors are proposed.

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Zhang, Yuan, and Ye Guo. "A Study on Rumor Propagation Model on Micro-Blogging Platforms." Advanced Materials Research 717 (July 2013): 808–11. http://dx.doi.org/10.4028/www.scientific.net/amr.717.808.

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Rumor is one of the principal factors to affect public sentiment. With the development of Internet, the group of the micro-bloggers continuously grows. The special propagation mode of micro-blogging brings challenge to the rumor management. This article summarizes the features of information dissemination of micro-blogging and has a review on the traditional rumor propagation models. Furthermore, the process of rumor propagation on the micro-blogging platform is deeply analyzed, the micro-bloggers in the process of rumor propagation are classified and the rumor propagation model on the micro-blogging platform is initially studied and established. The study of this article lays a foundation for further study on rumor management on the micro-blogging platform.

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Miyabe, Mai, Akiyo Nadamoto, and Eiji Aramaki. "How do rumors spread during a crisis?" International Journal of Web Information Systems 10, no. 4 (November 11, 2014): 394–412. http://dx.doi.org/10.1108/ijwis-04-2014-0015.

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Purpose – This aim of this paper is to elucidate rumor propagation on microblogs and to assess a system for collecting rumor information to prevent rumor-spreading. Design/methodology/approach – We present a case study of how rumors spread on Twitter during a recent disaster situation, the Great East Japan earthquake of March 11, 2011, based on comparison to a normal situation. We specifically examine rumor disaffirmation because automatic rumor extraction is difficult. Extracting rumor-disaffirmation is easier than extracting the rumors themselves. We classify tweets in disaster situations, analyze tweets in disaster situations based on users' impressions and compare the spread of rumor tweets in a disaster situation to that in a normal situation. Findings – The analysis results showed the following characteristics of rumors in a disaster situation. The information transmission is 74.9 per cent, representing the greatest number of tweets in our data set. Rumor tweets give users strong behavioral facilitation, make them feel negative and foment disorder. Rumors of a normal situation spread through many hierarchies but the rumors of disaster situations are two or three hierarchies, which means that the rumor spreading style differs in disaster situations and in normal situations. Originality/value – The originality of this paper is to target rumors on Twitter and to analyze rumor characteristics by multiple aspects using not only rumor-tweets but also disaffirmation-tweets as an investigation object.

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Liqing, Qiu, and Liu Shuqi. "SVIR rumor spreading model considering individual vigilance awareness and emotion in social networks." International Journal of Modern Physics C 32, no. 09 (April 28, 2021): 2150120. http://dx.doi.org/10.1142/s0129183121501205.

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Rumor, as a form of information, can be widely spread in a short time. A host of researchers focus on the spread of rumor, aiming to explore the rules of rumor spreading and put forward effective measures to help control the spread of rumor. In real life, when the individual is not interested in the rumor spread or feels that the rumor is not related to him, it is easy to trigger the individual’s vigilance awareness. On the contrary, if the rumor is more closely related to the individual’s life, the individual will usually be less alert and have great motivation to share it with friends. Based on the typical Susceptible–Infected–Recovered (SIR) model, a new vigilant state is added to describe the above phenomenon and a Susceptible–Vigilant–Infectious–Recovered (SVIR) rumor model is proposed. In addition, considering the fact that the infectious with high emotion may cause emotional resonance among individuals, this model adds a connection edge from the recovered to the infectious triggered by emotional infection. Based on the obtained dynamic equations, the steady state of the model is analyzed by utilizing basic reproduction number method and verified on the generated homogeneous network as well as Facebook network. Simulation results reveal that the improvement of individual vigilance awareness can reduce the influence of rumor. Although high emotional infectious can promote the spread of rumor, appealing them to clarify the fact for curbing rumor spreading is a forceful measure.

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Zhao, Hongyong, and Linhe Zhu. "Dynamic Analysis of a Reaction–Diffusion Rumor Propagation Model." International Journal of Bifurcation and Chaos 26, no. 06 (June 15, 2016): 1650101. http://dx.doi.org/10.1142/s0218127416501017.

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The rapid development of the Internet, especially the emergence of the social networks, leads rumor propagation into a new media era. Rumor propagation in social networks has brought new challenges to network security and social stability. This paper, based on partial differential equations (PDEs), proposes a new SIS rumor propagation model by considering the effect of the communication between the different rumor infected users on rumor propagation. The stabilities of a nonrumor equilibrium point and a rumor-spreading equilibrium point are discussed by linearization technique and the upper and lower solutions method, and the existence of a traveling wave solution is established by the cross-iteration scheme accompanied by the technique of upper and lower solutions and Schauder’s fixed point theorem. Furthermore, we add the time delay to rumor propagation and deduce the conditions of Hopf bifurcation and stability switches for the rumor-spreading equilibrium point by taking the time delay as the bifurcation parameter. Finally, numerical simulations are performed to illustrate the theoretical results.

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Chen, Jing, Nana Wei, Chen Xin, Mingxin Liu, Zeren Yu, and Miaomiao Liu. "Anti-Rumor Dissemination Model Based on Heat Influence and Evolution Game." Mathematics 10, no. 21 (November 1, 2022): 4064. http://dx.doi.org/10.3390/math10214064.

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Aiming at the problem that the existing rumor dissemination models only focus on the characteristics of rumor dissemination and ignore anti-rumor dissemination, an evolution game model, SDIR, based on heat influence is proposed in this paper. Firstly, in order to solve the problem that rumor and anti-rumor information of emergency events disseminate simultaneously in social networks, the model extracts the factors that affect information dissemination: user behavior characteristics, user closeness and heat influence of participating topics. Secondly, anti-rumor information and an evolutionary game mechanism are introduced into the traditional SIR model, binary information is introduced to analyze the anti-rumor dissemination model SDIR, and the four state transitions and dissemination processes of SDIR are discussed. Finally, the SDIR model is experimentally validated in different datasets and dissemination models. The experimental results show that the SDIR model is in line with the actual dissemination law, and it can be proved that high self-identification ability plays a certain role in suppressing rumors; the anti-rumor information effectively inhibits the spread of rumor information to a certain extent. Compared with other models, the SDIR model is closer to the real diffusion range in the dataset.

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Chen, Jianhong, Chaoqun Chen, Qinghua Song, Yifei Zhao, Longxin Deng, Raoqing Xie, and Shan Yang. "Spread Mechanism and Control Strategies of Rumor Propagation Model Considering Rumor Refutation and Information Feedback in Emergency Management." Symmetry 13, no. 9 (September 14, 2021): 1694. http://dx.doi.org/10.3390/sym13091694.

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The rumor-free equilibrium state and rumor-endemic equilibrium state are two symmetric descriptions of the status of a system. The constant spreading of rumors would affect the smooth operation of emergency management procedures and cause unnecessary social and economic loss. To reduce the negative effect of rumor propagation, in this paper, we introduce a compartmental model of rumor propagation, which considers the rumor refutation of public and information feedback. By deriving mean-field equations that describe the dynamics of the model, we use analytical and numerical solutions of these equations to investigate the threshold and dynamics of the model in both the closed system and open system. The results imply that the initial equilibrium point is not stable and there exists a rumor-free equilibrium point; in the open system, there exists a threshold beyond which rumors can spread; the stability of the initial equilibrium point is related to the threshold R0 = (φ*α)/μ, and there exists a rumor-endemic equilibrium point. The development process of rumor propagation can be divided into four stages: latent period, progressive period, intense period, and recession period. Under the influence of population, rumor spreading can exceed the threshold readily because the migration rate μ is usually less than the proportion of ignorants without critical ability φ, and the rumor spreading process in an open system presents a fluctuating development, the rumor would not disappear in this autonomous system. Based on the analysis, we propose some measures, such as providing open and efficient information queries and exchange platforms, etc.

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Zhao, Laijun, Xiaoli Wang, Jiajia Wang, Xiaoyan Qiu, and Wanlin Xie. "Rumor-Propagation Model with Consideration of Refutation Mechanism in Homogeneous Social Networks." Discrete Dynamics in Nature and Society 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/659273.

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In recent years, increasing attention has been paid to how to effectively manage rumor propagation. Based on previous studies of rumor propagation and some strategies used by the authorities to refute rumors and manage rumor propagation, we develop a new rumor-propagation model with consideration of refutation mechanism. In this paper, we describe the dynamic process of rumor propagation by accounting for the refutation mechanism in homogeneous social networks. And then, we derive mean-field equations for rumor-propagation process. We then analyze the stability of the model with respect to changes in parameter values. Our results show that there exists a critical thresholdλcthat is inversely proportional to the average degree of the social networks and is positively correlated with the strength of the refutation mechanism. If the spreading rate is bigger than the critical thresholdλc, rumors can be spread. Our numerical simulations in homogeneous networks demonstrate that increasing the ignorant’s refutation rateβcan reduce the peak value of spreaders density, which is better than increasing the spreader’s refutation rateη. Therefore, based on the seriousness of the rumor propagation and the rumor-propagation rate, the authorities can choose effective strategies that increase the refutation rate so that they can reduce the maximum influence of the rumor.

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Chen, Danroujing, Xiaoliang Chen, Peng Lu, Xuyang Wang, and Xiang Lan. "CNFRD: A Few-Shot Rumor Detection Framework via Capsule Network for COVID-19." International Journal of Intelligent Systems 2023 (February 27, 2023): 1–21. http://dx.doi.org/10.1155/2023/2467539.

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In recent years, COVID-19 has become the hottest topic. Various issues, such as epidemic transmission routes and preventive measures, have “occupied” several online social media platforms. Many rumors about COVID-19 have also arisen, causing public anxiety and seriously affecting normal social order. Identifying a rumor at its very inception is crucial to reducing the potential harm of its evolution to society as a whole. However, epidemic rumors provide limited signal features in the early stage. In order to identify rumors with data sparsity, we propose a few-shot learning rumor detection model based on capsule networks (CNFRD), utilizing the metric learning framework and the capsule network to detect the rumors posted during unexpected epidemic events. Specifically, we constructively use the capsule network neural layer to summarize the historical rumor data and obtain the generalized class representation based on the historical rumor data samples. Besides, we calculate the distance between the epidemic rumor sample and the historical rumor class-wise representation according to the metric module. Finally, epidemic rumors are discriminated against according to the nearest neighbor principle. The experimental results prove that the proposed method can achieve higher accuracy with fewer epidemic rumor samples. This approach provided 88.92% accuracy on the Chinese rumor dataset and 87.07% accuracy on the English rumor dataset, which improved by 7% to 23% over existing approaches. Therefore, the CNFRD model can identify epidemic rumors in COVID-19 as early as possible and effectively improve the performance of rumor detection.

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Chen, Jianhong, Qinghua Song, and Zhiyong Zhou. "Agent-Based Simulation of Rumor Propagation on Social Network Based on Active Immune Mechanism." Journal of Systems Science and Information 5, no. 6 (December 20, 2017): 571–84. http://dx.doi.org/10.21078/jssi-2017-571-14.

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AbstractTo simulate the rumor propagation process on online social network during emergency, a new rumor propagation model was built based on active immune mechanism. The rumor propagation mechanisms were analyzed and corresponding parameters were defined. BA scale free network and NW small world network that can be used for representing the online social network structure were constructed and their characteristics were compared. Agent-based simulations were conducted on both networks and results show that BA scale free network is more conductive to spreading rumors and it can facilitate the rumor refutation process at the same time. Rumors paid attention to by more people is likely to spread quicker and broader but for which the rumor refutation process will be more effective. The model provides a useful tool for understanding and predicting the rumor propagation process on online social network during emergency, providing useful instructions for rumor propagation intervention.

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Zhu, Linhe, Gui Guan, and Zhengdi Zhang. "Mathematical analysis of information propagation model in complex networks." International Journal of Modern Physics B 34, no. 26 (October 6, 2020): 2050240. http://dx.doi.org/10.1142/s0217979220502409.

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In virtue of identifying the influence of nodes, the spatial distance of rumor propagation is defined with the partition and clustering in the network. Considering the temporal and spatial propagation characteristics of rumors in online social networks, we establish a delayed rumor propagation model based on the graph theory and partial functional differential equations. Firstly, the unique existence and uniform boundedness of the nonnegative solution are explored. Secondly, we discuss the existence of positive equilibrium points sufficiently. Thirdly, stabilities of the rumor-free and rumor-spreading equilibrium points are investigated according to the linearization approach and Lyapunov function. Finally, we perform several numerical simulations to validate theoretical results and show the influence of time delay on rumor propagation. Experimental results further illustrate that taking forceful actions such as increasing the time delay in the rumor-spreading process can control rumor propagation due to the timely effectiveness of the information.

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He, Lingnan, Haoshen Yang, Xiling Xiong, and Kaisheng Lai. "Online Rumor Transmission Among Younger and Older Adults." SAGE Open 9, no. 3 (July 2019): 215824401987627. http://dx.doi.org/10.1177/2158244019876273.

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Social media not only leads to efficient dissemination of information but also facilitates the spread of rumors. However, it remains unknown whether and how WeChat use influences rumor transmission. Using a nationwide sample of Chinese adults ( N = 9,368), we applied a moderated mediation model to examine whether the relationship among WeChat use, rumor anxiety, and rumor transmission intention varies with age. Our findings show that frequent use of WeChat decreased young adults’ intention to transmit rumors by alleviating rumor anxiety, whereas in older adults, it increased this intention by increasing rumor anxiety. Among older adults, WeChat use had not only a direct effect on facilitating rumor transmission intention but also indirect effects through increased rumor anxiety. Our findings suggest that older adults are dissimilar from younger adults in terms of their level of vulnerability to believing rumors and the way they fall for rumors.

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Huo, Liang'an, Tingting Lin, and Peiqing Huang. "Dynamical Behavior of a Rumor Transmission Model with Psychological Effect in Emergency Event." Abstract and Applied Analysis 2013 (2013): 1–9. http://dx.doi.org/10.1155/2013/282394.

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A rumor transmission model with nonmonotonic incidence rate was proposed, which provides excellent explanations of the “psychological” effect with rumor spreading in emergency event. By carrying out a global analysis of the model and studying the stability of the rumor-free equilibrium and the rumor-endemic equilibrium, we showed that either the number of infective individuals tends to zero as time evolves or the rumor persists. Finally, recommendations for policy makers and consulting advice for related commissions are explored in the case study of crazy rumors propagated for the iodized sail shortage panic in China.

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Yao, Hongxing, and Xiangyang Gao. "SE2IR Invest Market Rumor Spreading Model Considering Hesitating Mechanism." Journal of Systems Science and Information 7, no. 1 (March 18, 2019): 54–69. http://dx.doi.org/10.21078/jssi-2019-054-16.

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Abstract According to the actual situation of investor network, a SE2IR rumor spreading model with hesitating mechanism is proposed, and the corresponding mean-field equations is obtained on scale-free network. In this paper, we first combine the theory of spreading dynamics and find out the basic reproductive number R0. And then analyzes the stability of the rumor-free equilibrium and the final rumor size. Finally, we discuss random immune strategies and target immune strategies for the rumor spreading, respectively. Through numerical simulation, we can draw the following conclusions: Reducing the fuzziness and attractiveness of invest market rumor can effectively reduce the impact of rumor. And the target immunization strategy is more effective than the random immunization strategy for the communicators in the invest investor network.

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Li, Chengcheng, Fengming Liu, and Pu Li. "Text Similarity Computation Model for Identifying Rumor Based on Bayesian Network in Microblog." International Arab Journal of Information Technology 17, no. 5 (September 1, 2020): 731–41. http://dx.doi.org/10.34028/iajit/17/5/6.

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The research of text similarity, especially for rumor texts, which constructed the calculation model by known rumors and calculated its similarity. From which, people can recognize the rumor in advance, and improve their vigilance to effectively block and control rumors dissemination. Based on the Bayesian network, the similarity calculation model of microblog rumor texts was built. At the same time, taking into account not only the rumor texts have similar characters, but also the rumor producers have similar characters, and therefore the similarity calculation model of rumor texts makers was constructed. Then, the similarity between the text and the user was integrated, and the microblog similarity calculation model was established. Finally, also experimentally studied the performance of the proposed model on the microblog rumor text and the user data set. The experimental results indicated that the similarity algorithm proposed in this paper could be used to identify the rumors of texts and predict the characters of users more accurately and effectively

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Khanifar, Hossein, Gholamreza Jandaghi, Hamed Bordbar, and Mahmoud Jangholi. "Clarifying ethical constituents of God-believing employees to mitigate the outcomes of rumors and organizational rumor management." International Journal of Human Resource Studies 2, no. 1 (January 29, 2012): 100. http://dx.doi.org/10.5296/ijhrs.v2i1.1166.

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By declining human spiritual belongings, the lack of ethics is considered as a major calamity of modern age. Disrespecting ethical codes and constituents in organizations and societies has caused that some ethical abnormal to be highlighted and involve the mind of managers and relevant authorities. Human get away of God believing and ethics – orientation as well as the lack of a clear and precise definition of ethical prism in organizations have caused unethical rumor behavior. Rumor is an unethical behavior disseminated among people in order to be believed. It is disseminated from one person to another verbally without any document. It causes that organizational managers and officials emphasize on human God-believing nature to mitigate the rumor negative outcomes and rumor management. While defining the rumor, present paper addresses to etiology of rumor in local and international literature and finally points ethical constituents which mitigate organizational rumor and abnormal behaviors in the organization.

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Liu, Qianqian, Gang Shi, and Yuhong Sheng. "An uncertain SEIR rumor model." Journal of Intelligent & Fuzzy Systems 41, no. 1 (August 11, 2021): 399–412. http://dx.doi.org/10.3233/jifs-201865.

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In this paper, an uncertain SEIR rumor model driven by one uncertain process is formulated to investigate the influence of perturbation in the transmission of rumor. Firstly, the deduced process of the uncertain SEIR rumor model is presented. Then, we proposed the existence and uniqueness theorem for the solution of the model. Moreover, the study of the stability of the uncertain SEIR rumor model was carried out, and then we came to the conclusion that the model stable in mean. In addition, computer algorithm and numerical simulation is used to verify the accuracy of the theoretical results. The simulation results show that the proposed model can explain the trend of rumor propagation correctly and describe the rumor propagation accurately. Finally, we have compared the propagation process of the uncertain rumor model and the deterministic model according to the numerical algorithm, and drew the conclusion that the model with uncertain perturbation fluctuates around the deterministic model.

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Huo, Liang'an, Peiqing Huang, and Chun-xiang Guo. "Analyzing the Dynamics of a Rumor Transmission Model with Incubation." Discrete Dynamics in Nature and Society 2012 (2012): 1–21. http://dx.doi.org/10.1155/2012/328151.

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This paper considers a rumor transmission model with incubation that incorporates constant recruitment and has infectious force in the latent period and infected period. By carrying out a global analysis of the model and studying the stability of the rumor-free equilibrium and the rumor-endemic equilibrium, we use the geometric approach for ordinary differential equations which is based on the use of higher-order generalization of Bendixson’s criterion. It shows that either the number of rumor infective individuals tends to zero as time evolves or the rumor persists. We prove that the transcritical bifurcation occurs atR0crosses the bifurcation thresholdR0=1by projecting the flow onto the extended center manifold. Since the rumor endemic level at the equilibrium is a continuous function ofR0, as a consequence for successful eradication of the rumor, one should simply reduceR0continuously below the threshold value 1. Finally, the obtained results are numerically validated and then discussed from both the mathematical and the sociological perspectives.

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Zhao, Haifeng, Bin Lin, and Chongqing Guo. "A Mathematics Model for Quantitative Analysis of Demand Disruption Caused by Rumor Spreading." International Journal of Information Technology & Decision Making 13, no. 03 (May 2014): 585–602. http://dx.doi.org/10.1142/s0219622014500515.

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Rumors greatly impact consumers' attitudes and purchasing intention. Rumor spreading can disrupt supply chain demand, particularly in today's Internet age. We propose a mathematical model for the quantitative analysis of demand disruption caused by rumor spreading based on the susceptible-infective-isolated-immune (SI2I) rumor spreading model, which extends the susceptible-infective-recovered (SIR) rumor spreading model by dividing stiflers into isolators and immunes. Both groups represent individuals who do not propagate a rumor, but the former believes the rumor while the latter does not. From the firms' perspective, only ignorants and immunes will still purchase their products and services after a rumor has spread. Hence, the influence of rumors on demand can be quantitatively reflected by the proportion of ignorants and immunes in the population. This study offers a new method for company managers to predict the variation trend of demand and estimate demand loss when a firm is attacked by rumors.

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Yang, Feng, Yunyue Ren, Shusheng Wang, and Xiaoqian Zhang. "Health-Related Rumor Control through Social Collaboration Models: Lessons from Cases in China during the COVID-19 Pandemic." Healthcare 10, no. 8 (August 5, 2022): 1475. http://dx.doi.org/10.3390/healthcare10081475.

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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.

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Chen, Jing, Nana Wei, and Hongbo Yang. "Immune Algorithm to Suppress Rumor Propagation Based on Influence Maximization." Security and Communication Networks 2022 (April 22, 2022): 1–13. http://dx.doi.org/10.1155/2022/6785828.

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In order to effectively reduce the spread range of rumor information, an immune method based on two-stage influence maximization to suppress rumor propagation is proposed. Firstly, User and Clustering Influence Maximizing (UCIM) algorithm is proposed to obtain the most influence node set at the current moment in the initial stage of event evolution based on the network topology and user characteristics. Secondly, the node set is identified and classified based on the RNN rumor detection model, and Immunosuppression Strategy considering the Average Path Weights and User-Clustering (IS-APWUC) strategy is proposed for the identified rumor nodes. In this strategy, rumor node set is taken as root nodes, and neighbor nodes with weak influence are pruned to construct an effective rumor path tree. Thirdly, considering the total probability of being infected by the rumors and the comprehensive influence factors, the nodes with high influence in the propagation stage are calculated as immune nodes so as to block the spread of the rumor information. Finally, the proposed method is verified by experiments on four real-world datasets. The results show that the IS-APWUC method has a better rumor suppression effect than the similar correlation algorithms.

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Choi, Jiho, Taewook Ko, Younhyuk Choi, Hyungho Byun, and Chong-kwon Kim. "Dynamic graph convolutional networks with attention mechanism for rumor detection on social media." PLOS ONE 16, no. 8 (August 18, 2021): e0256039. http://dx.doi.org/10.1371/journal.pone.0256039.

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Social media has become an ideal platform for the propagation of rumors, fake news, and misinformation. Rumors on social media not only mislead online users but also affect the real world immensely. Thus, detecting the rumors and preventing their spread became an essential task. Some of the recent deep learning-based rumor detection methods, such as Bi-Directional Graph Convolutional Networks (Bi-GCN), represent rumor using the completed stage of the rumor diffusion and try to learn the structural information from it. However, these methods are limited to represent rumor propagation as a static graph, which isn’t optimal for capturing the dynamic information of the rumors. In this study, we propose novel graph convolutional networks with attention mechanisms, named Dynamic GCN, for rumor detection. We first represent rumor posts with their responsive posts as dynamic graphs. The temporal information is used to generate a sequence of graph snapshots. The representation learning on graph snapshots with attention mechanism captures both structural and temporal information of rumor spreads. The conducted experiments on three real-world datasets demonstrate the superiority of Dynamic GCN over the state-of-the-art methods in the rumor detection task.

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Cheng, Yingying, Liang’an Huo, Liang Ma, and Hongyuan Guo. "Dynamical behaviors and spatial diffusion in a psychologically realistic rumor spreading model." International Journal of Modern Physics C 31, no. 02 (January 21, 2020): 2050034. http://dx.doi.org/10.1142/s0129183120500345.

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The spread of rumors has caused serious social and economic problems, especially during emergencies. Reducing the harm caused by rumors requires understanding the dynamical mechanism by which they propagate. To include the influence of time-dependent psychological factors, this paper proposes an improved rumor spreading model and derives mean-field equations describing the dynamics of rumor spreading. The psychological factors considered are the attenuation of individual interest, the cumulative effect of memory, and changes in sensory intensity with time. We also obtain the threshold condition of rumor spreading. Numerical simulations are used to verify our theoretical results. It is proved that the extremum of the cumulative effect of memory and the rumor attraction rate are positively correlated with the peak number of rumor spreaders, and negatively with the time required to reach the final rumor size. Time grows geometrically, while sensory intensity grows arithmetically. The initial approval rate of the memory accumulation effect and the stifling mechanism have little effect on the final rumor size. Finally, it is found that increasing the attenuation of interest coefficient reduces the time needed for the rumor to reach its final size.

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Qiu, Liqing, and Shuqi Liu. "C-SIW Rumor Propagation Model with Variable Propagation Rate and Perception Mechanism in Social Networks." Discrete Dynamics in Nature and Society 2020 (August 5, 2020): 1–12. http://dx.doi.org/10.1155/2020/5712968.

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The propagation of rumor has become a common phenomenon in social networks. Studying the dynamic propagation of rumor can help locate the key points to control rumor propagation. To further research the internal motivation of state transition, a corrector-ignorant-spreader-weakener (C-SIW) model is proposed in this paper. When the individual changes state to transmit rumor, the neighbor may have a significant impact on rumor propagation. Considering the point, this paper constructs a function to describe the propagation rate, which relates to the state of neighbors and the reputation of the spreader. In addition, perception from life also can cause individual state changes. Based on the above fact, the links from the spreader and the weakener to the corrector are added to describe the perception mechanism. Then, combining the derived average field equations, the steady state of the model is analyzed and verified in experimental simulation. Moreover, the experimental results on different networks show that the perception mechanism reduces the rumor influence. Besides, the variable propagation rate can position the fast-growing stage of rumor propagation more accurately and facilitate the control of rumor propagation.

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Sun, Rui, and Wan Bo Luo. "Rumor Propagation Model for Complex Network with Non-Uniform Propagation Rates." Applied Mechanics and Materials 596 (July 2014): 868–72. http://dx.doi.org/10.4028/www.scientific.net/amm.596.868.

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Considering propagation characteristics and affecting factors of rumor in real-world complex networks, this paper described different propagation rates of different nodes by introducing the rumor acceptability function. Based on mean-field theory, this paper presented a rumor propagation model with non-uniform propagation rate, and then simulated the behaviour of rumor propagation on scale-free network and calculated the propagation thresholds by corresponding dynamics equation. Theoretical analysis and simulation results show that nodes with different rumor acceptability could lead to slowing the spread of rumors, make positive propagation threshold arise, and effectively contain the outbreak and reduce the risk of rumors.

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Li, Chunru, and Zujun Ma. "Dynamics Analysis and Optimal Control for a Delayed Rumor-Spreading Model." Mathematics 10, no. 19 (September 22, 2022): 3455. http://dx.doi.org/10.3390/math10193455.

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In this work, we analyze a delayed rumor-propagation model. First, we analyze the existence and boundedness of the solution of the model. Then, we give the conditions for the existence of the rumor-endemic equilibrium. Regrading the delay as a bifurcating parameter, we explore the local asymptotic stability and Hopf bifurcation of the rumor-endemic equilibrium. By a Lyapunov functional technique, we examine the global asymptotically stability of the rumor-free and the rumor-endemic equilibria. We provide two control variables in the rumor-spreading model with time delay, and get the optimal solution via the optimal procedures. Finally, we present some numerical simulations to verify our theoretical predictions. They illustrate that the delay is a crucial issue for system, and it can lead to not just Hopf bifurcation but also chaos.

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Nærum, Knut. "Knuts ruter." Samtiden 118, no. 02 (November 5, 2009): 136. http://dx.doi.org/10.18261/issn1890-0690-2009-02-15.

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Nærum, Knut. "Knuts ruter." Samtiden 118, no. 03 (January 1, 2010): 116. http://dx.doi.org/10.18261/issn1890-0690-2009-03-12.

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Bhosale, Yogesh J., Mayuresh B. Kedari, Tejas V. Tarawade, and Abhishek S. Late. "Rumor Detection." International Journal of Recent Technology and Engineering (IJRTE) 10, no. 2 (July 30, 2021): 14–16. http://dx.doi.org/10.35940/ijrte.b6073.0710221.

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Everyone has internet access and is connected to social media in today's fast-paced world. Numerous pieces of data are disseminated on these websites, but there is no reliable source for confirmation or verification. This is where rumors come into play. Rumors are deliberate fabrications intended to sway or drastically alter popular opinion, and their impact can be seen in politics, especially during elections, and on social media. Thus, to resolve this problem, a rumor detector is needed that is capable of accurately indicating whether information is false or real. We implemented algorithms such as Multinomial Naive Bayes, Gradient Boosting, and Random Forest on complex datasets to get this Rumor Detection System closer to more reliable rumor performance. Accuracy of Multinomial Naive Bayes is approximately 90.4Forestitwas86.588.3

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Tommaso, Mario. "Arruído rumor." Opiniães 1, no. 1 (December 17, 2010): 140. http://dx.doi.org/10.11606/issn.2525-8133.opiniaes.2010.119109.

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O Programa de Pós-graduação em Literatura Brasileira da Universidade de São Paulo, em projeto ﬁ nanciado pela CAPES através do PROEX, lançou, em 2008, a Série Teses e Dissertações. A coleção reúne dezesseis trabalhos apresentados para o obtenção de títulos de Mestre e Doutor em Literatura Brasileira, produzidos durante os dois anos anteriores. Foram contempladas as diversas linhas de pesquisa atualmente em vigor, representando uma importante diversidade em termos de períodos e gêneros literários, bem como diversas abordagens metodológicas e modalidades de discurso crítico. Os exemplares não são comercializados, mas podem ser encontrados nas mais importantes bibliotecas públicas do país. O projeto, idealizado pelo professor Jaime Ginzburg, tem como objetivo dar maior visibilidade aos trabalhos acadêmicos, valorizando o livro como forma privilegiada de circulação do material.

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Weiner, S. "The Rumor." Labor Studies in Working-Class History of the Americas 9, no. 1 (March 1, 2012): 5. http://dx.doi.org/10.1215/15476715-1460597.

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Vosoughi, Soroush, Mostafa ‘Neo’ Mohsenvand, and Deb Roy. "Rumor Gauge." ACM Transactions on Knowledge Discovery from Data 11, no. 4 (August 21, 2017): 1–36. http://dx.doi.org/10.1145/3070644.

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Shah, Devavrat, and Tauhid Zaman. "Rumor centrality." ACM SIGMETRICS Performance Evaluation Review 40, no. 1 (June 7, 2012): 199–210. http://dx.doi.org/10.1145/2318857.2254782.

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Uzun, Gunalp, and Mesut Mutluoglu. "Dependent Rubor." New England Journal of Medicine 364, no. 26 (June 30, 2011): e56. http://dx.doi.org/10.1056/nejmicm1010160.

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Arata, I. "Rumor City." South Atlantic Quarterly 106, no. 4 (October 1, 2007): 859–69. http://dx.doi.org/10.1215/00382876-2007-051.

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Journal articles on the topic 'Rutor'

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