Journal articles on the topic 'Rumour Spreading'
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Sun, Zhonggen, Xin Cheng, Ruilian Zhang, and Bingqing Yang. "Factors Influencing Rumour Re-Spreading in a Public Health Crisis by the Middle-Aged and Elderly Populations." International Journal of Environmental Research and Public Health 17, no. 18 (September 8, 2020): 6542. http://dx.doi.org/10.3390/ijerph17186542.
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Due to discrimination and media literacy, middle-aged and elderly individuals have been easily reduced to marginalized groups in the identification of rumours during a public health crisis and can easily spread rumours repeatedly, which has a negative impact on pandemic prevention and social psychology. To further clarify the factors influencing their behaviours, this study used a questionnaire to survey a sample of 556 individuals in China and used multiple linear regression and analysis of variance to explore influencing factors during the coronavirus disease 2019 (COVID-19) pandemic. We found that, first, in the COVID-19 pandemic, middle-aged and elderly adults’ willingness to re-spread rumours is positively related to their degree of believing rumours and to personal anxiety and is negatively related to their rumour-discrimination ability and to their perception of serious consequences to rumour spreading. Second, the degree of believing rumours plays an intermediary role in the willingness to re-spread rumours. It plays a partial mediating role in the path of anxiety’s influence on behaviour, suggesting that an anxious person will spread a rumour even if he or she does not have a strong belief in the rumour. Third, interpersonal communication has a greater credibility and a greater willingness to re-spread than does mass communication. This suggests the importance of increasing public knowledge expertise and of reducing public panic. This also has important implications for the future design of public health policies.
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Niranjan, Utkarsh, Anurag Singh, and Ramesh Kumar Agrawal. "A mean-field-theoretic model for dual information propagation in networks." Journal of Complex Networks 7, no. 4 (January 7, 2019): 585–602. http://dx.doi.org/10.1093/comnet/cny033.
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Abstract The Internet is a place where a vast amount of information is flowing. With the deeper penetration of social media, everybody is participating in spreading information. Often we find ourselves confused with competing information on the same topic. In this work, we present a novel model for competitive information diffusion on the scale-free network. The proposed model is an extension of the classical DK model of rumour spreading. Most of previous competitive information diffusion models consider a different type of stiflers to be similar. In our model we have two separate compartments for different types of stiflers. We present a detailed analysis about the effect of infection rate on the prevalence of rumour in the network. To capture the large chunk of population one requires relatively higher spreading rate. Relative impact of spreading rate and stifler rate on the final population in different compartments is also presented. In our analysis, we find that if stifler rate is higher than the spreading rate, a large portion of population remains unaware of rumours. We also find that if the information source is a popular person than people have a bias towards that information and information coming from less popular persons lose its grip on the network and lose the competition. This analysis illustrates that why big companies hire famous celebrities to promote their products. We also demonstrate rumour spreading analysis with numerical solution, network simulation and real network topology of Facebook.
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PANAGIOTOU, KONSTANTINOS, XAVIER PÉREZ-GIMÉNEZ, THOMAS SAUERWALD, and HE SUN. "Randomized Rumour Spreading: The Effect of the Network Topology." Combinatorics, Probability and Computing 24, no. 2 (May 6, 2014): 457–79. http://dx.doi.org/10.1017/s0963548314000194.
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We consider the popular and well-studied push model, which is used to spread information in a given network with n vertices. Initially, some vertex owns a rumour and passes it to one of its neighbours, which is chosen randomly. In each of the succeeding rounds, every vertex that knows the rumour informs a random neighbour. It has been shown on various network topologies that this algorithm succeeds in spreading the rumour within O(log n) rounds. However, many studies are quite coarse and involve huge constants that do not allow for a direct comparison between different network topologies. In this paper, we analyse the push model on several important families of graphs, and obtain tight runtime estimates. We first show that, for any almost-regular graph on n vertices with small spectral expansion, rumour spreading completes after log2n + log n+o(log n) rounds with high probability. This is the first result that exhibits a general graph class for which rumour spreading is essentially as fast as on complete graphs. Moreover, for the random graph G(n,p) with p=c log n/n, where c > 1, we determine the runtime of rumour spreading to be log2n + γ (c)log n with high probability, where γ(c) = clog(c/(c−1)). In particular, this shows that the assumption of almost regularity in our first result is necessary. Finally, for a hypercube on n=2d vertices, the runtime is with high probability at least (1+β) ⋅ (log2n + log n), where β > 0. This reveals that the push model on hypercubes is slower than on complete graphs, and thus shows that the assumption of small spectral expansion in our first result is also necessary. In addition, our results combined with the upper bound of O(log n) for the hypercube (see [11]) imply that the push model is faster on hypercubes than on a random graph G(n, clog n/n), where c is sufficiently close to 1.
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Angel, Omer, Abbas Mehrabian, and Yuval Peres. "The string of diamonds is nearly tight for rumour spreading." Combinatorics, Probability and Computing 29, no. 2 (November 4, 2019): 190–99. http://dx.doi.org/10.1017/s0963548319000385.
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AbstarctFor a rumour spreading protocol, the spread time is defined as the first time everyone learns the rumour. We compare the synchronous push&pull rumour spreading protocol with its asynchronous variant, and show that for any n-vertex graph and any starting vertex, the ratio between their expected spread times is bounded by $O({n^{1/3}}{\log ^{2/3}}n)$. This improves the $O(\sqrt n)$ upper bound of Giakkoupis, Nazari and Woelfel (2016). Our bound is tight up to a factor of O(log n), as illustrated by the string of diamonds graph. We also show that if, for a pair α, β of real numbers, there exist infinitely many graphs for which the two spread times are nα and nβ in expectation, then $0 \le \alpha \le 1$ and $\alpha \le \beta \le {1 \over 3} + {2 \over 3} \alpha $; and we show each such pair α, β is achievable.
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Nekovee, M., Y. Moreno, G. Bianconi, and M. Marsili. "Theory of rumour spreading in complex social networks." Physica A: Statistical Mechanics and its Applications 374, no. 1 (January 2007): 457–70. http://dx.doi.org/10.1016/j.physa.2006.07.017.
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Ostilli, Massimo, Eiko Yoneki, Ian X. Y. Leung, Jose F. F. Mendes, Pietro Lió, and Jon Crowcroft. "Statistical mechanics of rumour spreading in network communities." Procedia Computer Science 1, no. 1 (May 2010): 2331–39. http://dx.doi.org/10.1016/j.procs.2010.04.262.
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Zhang, Zi-li, and Zi-qiong Zhang. "An interplay model for rumour spreading and emergency development." Physica A: Statistical Mechanics and its Applications 388, no. 19 (October 2009): 4159–66. http://dx.doi.org/10.1016/j.physa.2009.06.020.
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Doerr, Benjamin, and Mahmoud Fouz. "A Time-Randomness Tradeoff for Quasi-Random Rumour Spreading." Electronic Notes in Discrete Mathematics 34 (August 2009): 335–39. http://dx.doi.org/10.1016/j.endm.2009.07.055.
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Belen, Selma, C. Yalçin Kaya, and C. E. M. Pearce. "Impulsive control of rumours with two broadcasts." ANZIAM Journal 46, no. 3 (January 2005): 379–91. http://dx.doi.org/10.1017/s1446181100008324.
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AbstractIn this paper we introduce an impulsive control model of a rumour process. The spreaders are classified as subscriber spreaders, who receive an initial broadcast of a rumour and start spreading it, and nonsubscriber spreaders who change from being an ignorant to being a spreader after encountering a spreader. There are two consecutive broadcasts. The first starts the rumour process. The objective is to time the second broadcast so that the final proportion of ignorants is minimised. The second broadcast reactivates as spreaders either the subscriber stiflers (Scenario 1) or all individuals who have been spreaders (Scenario 2). It is shown that with either scenario the optimal time for the second broadcast is always when the proportion of spreaders drops to zero.
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de Arruda, Guilherme Ferraz, Elcio Lebensztayn, Francisco A. Rodrigues, and Pablo Martín Rodríguez. "A process of rumour scotching on finite populations." Royal Society Open Science 2, no. 9 (September 2015): 150240. http://dx.doi.org/10.1098/rsos.150240.
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Rumour spreading is a ubiquitous phenomenon in social and technological networks. Traditional models consider that the rumour is propagated by pairwise interactions between spreaders and ignorants. Only spreaders are active and may become stiflers after contacting spreaders or stiflers. Here we propose a competition-like model in which spreaders try to transmit an information, while stiflers are also active and try to scotch it. We study the influence of transmission/scotching rates and initial conditions on the qualitative behaviour of the process. An analytical treatment based on the theory of convergence of density-dependent Markov chains is developed to analyse how the final proportion of ignorants behaves asymptotically in a finite homogeneously mixing population. We perform Monte Carlo simulations in random graphs and scale-free networks and verify that the results obtained for homogeneously mixing populations can be approximated for random graphs, but are not suitable for scale-free networks. Furthermore, regarding the process on a heterogeneous mixing population, we obtain a set of differential equations that describes the time evolution of the probability that an individual is in each state. Our model can also be applied for studying systems in which informed agents try to stop the rumour propagation, or for describing related susceptible–infected–recovered systems. In addition, our results can be considered to develop optimal information dissemination strategies and approaches to control rumour propagation.
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Pittel, B. "On a Daley-Kendall model of random rumours." Journal of Applied Probability 27, no. 1 (March 1990): 14–27. http://dx.doi.org/10.2307/3214592.
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Suppose that a certain population consists of N individuals. One member initially learns a rumour from an outside source, and starts telling it to other members, who continue spreading the information. A knower becomes inactive once he encounters somebody already informed. Daley and Kendall, who initiated the study of this model, conjectured that the number of eventual knowers is asymptotically normal with mean and variance linear in N. Our purpose is to confirm this conjecture.
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Pittel, B. "On a Daley-Kendall model of random rumours." Journal of Applied Probability 27, no. 01 (March 1990): 14–27. http://dx.doi.org/10.1017/s0021900200038390.
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Suppose that a certain population consists of N individuals. One member initially learns a rumour from an outside source, and starts telling it to other members, who continue spreading the information. A knower becomes inactive once he encounters somebody already informed. Daley and Kendall, who initiated the study of this model, conjectured that the number of eventual knowers is asymptotically normal with mean and variance linear in N. Our purpose is to confirm this conjecture.
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Ferraz de Arruda, Guilherme, Francisco Aparecido Rodrigues, Pablo Martín Rodríguez, Emanuele Cozzo, and Yamir Moreno. "A general Markov chain approach for disease and rumour spreading in complex networks." Journal of Complex Networks 6, no. 2 (August 2, 2017): 215–42. http://dx.doi.org/10.1093/comnet/cnx024.
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Svensson, Åke. "On the asymptotic size and duration of a class of epidemic models." Journal of Applied Probability 32, no. 1 (March 1995): 11–24. http://dx.doi.org/10.2307/3214917.
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Models for epidemic spread of infections are formulated by defining intensities for relevant counting processes. It is assumed that an infected individual passes through k stages of infectivity. The times spent in the different stages are random. Many well-known models for the spread of infections can be described in this way. The models can also be applied to describe other processes of epidemic character (such as models for rumour spreading). Asymptotic results are derived both for the size and for the duration of the epidemic.
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Svensson, Åke. "On the asymptotic size and duration of a class of epidemic models." Journal of Applied Probability 32, no. 01 (March 1995): 11–24. http://dx.doi.org/10.1017/s0021900200102530.
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Models for epidemic spread of infections are formulated by defining intensities for relevant counting processes. It is assumed that an infected individual passes through k stages of infectivity. The times spent in the different stages are random. Many well-known models for the spread of infections can be described in this way. The models can also be applied to describe other processes of epidemic character (such as models for rumour spreading). Asymptotic results are derived both for the size and for the duration of the epidemic.
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Zhu, Linhe, and Hongyong Zhao. "Dynamical behaviours and control measures of rumour-spreading model with consideration of network topology." International Journal of Systems Science 48, no. 10 (April 11, 2017): 2064–78. http://dx.doi.org/10.1080/00207721.2017.1312628.
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FOX, ADAM. "RUMOUR, NEWS AND POPULAR POLITICAL OPINION IN ELIZABETHAN AND EARLY STUART ENGLAND." Historical Journal 40, no. 3 (September 1997): 597–620. http://dx.doi.org/10.1017/s0018246x97007346.
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This essay explores the circulation of rumour and news among those at the lower levels of society in late sixteenth- and early seventeenth-century England. It does so through an analysis of the court records in which people were indicted for spreading false reports or speaking seditious words and which are now preserved in assize files or amid the state papers. These sources reveal the networks of communication by which information was disseminated nationwide and shed light upon the relationship between oral, manuscript and printed media. They show how wild stories could be whipped up in the act of transmission and were fuelled by the political insecurities of this period. At the same time a more sophisticated awareness of current affairs is evident in some illicit conversations which suggest that even humble people were participating in the arguments which anticipated the Civil War.
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Bhansali, Rinni, and Laura P. Schaposnik. "A trust model for spreading gossip in social networks: a multi-type bootstrap percolation model." Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 476, no. 2235 (March 2020): 20190826. http://dx.doi.org/10.1098/rspa.2019.0826.
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We introduce here a multi-type bootstrap percolation model, which we call T -Bootstrap Percolation ( T -BP), and apply it to study information propagation in social networks. In this model, a social network is represented by a graph G whose vertices have different labels corresponding to the type of role the person plays in the network (e.g. a student, an educator etc.). Once an initial set of vertices of G is randomly selected to be carrying a gossip (e.g. to be infected), the gossip propagates to a new vertex provided it is transmitted by a minimum threshold of vertices with different labels. By considering random graphs, which have been shown to closely represent social networks, we study different properties of the T -BP model through numerical simulations, and describe its implications when applied to rumour spread, fake news and marketing strategies.
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Li, Jin, Renbin Xiao, and Huimin Wang. "A social computing approach to rumour spreading with consideration of illusory truth effect and the latency reverse phenomenon." International Journal of Innovative Computing and Applications 7, no. 2 (2016): 61. http://dx.doi.org/10.1504/ijica.2016.077581.
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Topîrceanu, Alexandru. "Competition-Based Benchmarking of Influence Ranking Methods in Social Networks." Complexity 2018 (August 16, 2018): 1–15. http://dx.doi.org/10.1155/2018/4562609.
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The development of new methods to identify influential spreaders in complex networks has been a significant challenge in network science over the last decade. Practical significance spans from graph theory to interdisciplinary fields like biology, sociology, economics, and marketing. Despite rich literature in this direction, we find small notable effort to consistently compare and rank existing centralities considering both the topology and the opinion diffusion model, as well as considering the context of simultaneous spreading. To this end, our study introduces a new benchmarking framework targeting the scenario of competitive opinion diffusion; our method differs from classic SIR epidemic diffusion, by employing competition-based spreading supported by the realistic tolerance-based diffusion model. We review a wide range of state-of-the-art node ranking methods and apply our novel method on large synthetic and real-world datasets. Simulations show that our methodology offers much higher quantitative differentiation between ranking methods on the same dataset and notably high granularity for a ranking method over different datasets. We are able to pinpoint—with consistency—which influence the ranking method performs better against the other one, on a given complex network topology. We consider that our framework can offer a forward leap when analysing diffusion characterized by real-time competition between agents. These results can greatly benefit the tackling of social unrest, rumour spreading, political manipulation, and other vital and challenging applications in social network analysis.
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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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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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Vlachou, Maria, Kafenia Botsoglou, and Eleni Andreou. "Assessing Bully/Victim Problems in Preschool Children: A Multimethod Approach." Journal of Criminology 2013 (June 23, 2013): 1–8. http://dx.doi.org/10.1155/2013/301658.
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Studies addressing the issue of bullying during the preschool period are still extremely rare. The main aim of the present research was to study the prevalence rates of bullying in preschool children using a multimethod approach. Participants were 167 preschool children (ages 4–6) and 8 classroom teachers. Measures were four forms of bullying: verbal, physical, and relational bullying and rumour spreading. Data were collected through peer nominations, self- and teacher reports, and natural observations. Results have shown that the frequencies of bullying episodes vary greatly according to the source of information. Moreover, agreement between informants was either nonsignificant or moderate. This is extremely important when conducting relevant empirical research with preschool populations. It is probable that inconsistent results obtained in previous research may be due to the selection of one or another source of information. It is of primary importance to design methodological tools that are both valid and reliable if prevention programs against victimisation are to be consistent and effective.
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Xin, Yanwen, and Fengming Liu. "Rumor Situation Discrimination Based on Empirical Mode Decomposition Correlation Dimension." Complexity 2021 (April 23, 2021): 1–12. http://dx.doi.org/10.1155/2021/5541987.
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To effectively identify network rumors and block their spread, this paper uses fractal theory to analyze a network rumor spreading situation time series, reveal its inner regularity, extract features, and establish a network rumor recognition model. The model is based on an empirical mode decomposition (EMD) correlation dimension and K-nearest neighbor (KNN) approach. Firstly, a partition function is used to determine if the time series of the rumor spreading situation is a uniform fractal process. Secondly, the rumor spreading situation is subjected to EMD to obtain a series of intrinsic mode functions (IMFs), construct the IMF1–IMF6 components containing effective feature information as the principal components, and reconstruct the phase space of the principal components, respectively. Finally, the correlation dimensions of the principal components IMF1–IMF6 as obtained by the Grassberger-Procaccia algorithm are used as feature parameters and are imported into the KNN model for rumor recognition. The experimental results show that the correlation dimension of a spreading situation can better reflect the characteristic information; as combined with the KNN model for identifying rumors, the recognition rate reaches 87.5%. This result verifies the effectiveness of fractal theory in network rumors recognition, expands the thinking for the research of rumors recognition, and provides theoretical support for rumor governance.
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Jiang, Ping, and Xiangbin Yan. "Stability analysis and control models for rumor spreading in online social networks." International Journal of Modern Physics C 28, no. 05 (March 9, 2017): 1750061. http://dx.doi.org/10.1142/s0129183117500619.
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This paper establishes a novel Susceptible-Infected-Removed (SIR) rumor spreading model for online social networks (OSNs). The model utilizes the node degree to describe the dynamic changes of the number of rumor spreaders and it can be regarded as an extension of the traditional SIR model. Stability analysis of the model reveals that the spreader in social networks has a basic reproduction number. If the basic reproduction number is less than 1, then rumors will disappear. Otherwise, rumors will persist. According to this result, we can predict the trend of rumor spreading. Then we propose an immune-structure SIR model to explore the control method of rumor spreading. Stability analysis and numerical simulation of the model indicate that immunizing susceptible individual is an effective method to control rumors. Further, the immune-structure model explains that the network structure decides the choice of immune methods. Our findings offer some new insights to control the spread of rumors on OSNs.
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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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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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Jahanbakhsh-Nagadeh, Zoleikha, Mohammad-Reza Feizi-Derakhshi, and Arash Sharifi. "A Deep Content-Based Model for Persian Rumor Verification." ACM Transactions on Asian and Low-Resource Language Information Processing 21, no. 1 (January 31, 2022): 1–29. http://dx.doi.org/10.1145/3487289.
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During the development of social media, there has been a transformation in social communication. Despite their positive applications in social interactions and news spread, it also provides an ideal platform for spreading rumors. Rumors can endanger the security of society in normal or critical situations. Therefore, it is important to detect and verify the rumors in the early stage of their spreading. Many research works have focused on social attributes in the social network to solve the problem of rumor detection and verification, while less attention has been paid to content features. The social and structural features of rumors develop over time and are not available in the early stage of rumor. Therefore, this study presented a content-based model to verify the Persian rumors on Twitter and Telegram early. The proposed model demonstrates the important role of content in spreading rumors and generates a better-integrated representation for each source rumor document by fusing its semantic, pragmatic, and syntactic information. First, contextual word embeddings of the source rumor are generated by a hybrid model based on ParsBERT and parallel CapsNets. Then, pragmatic and syntactic features of the rumor are extracted and concatenated with embeddings to capture the rich information for rumor verification. Experimental results on real-world datasets demonstrated that the proposed model significantly outperforms the state-of-the-art models in the early rumor verification task. Also, it can enhance the performance of the classifier from 2% to 11% on Twitter and from 5% to 23% on Telegram. These results validate the model's effectiveness when limited content information is available.
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Al-Ameedi, Riyadh Tariq Kadhim, and Mohanned Jaasim Dakhil Al-Ghizzy. "Investigating Cyberbullying in Electronic Communication: A Descriptive Study." International Journal of English Language Studies 4, no. 4 (December 18, 2022): 97–106. http://dx.doi.org/10.32996/ijels.2022.4.4.13.
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Cyberbullying is widely used nowadays in electronic communication. It takes different forms, and it is considered a serious problem that faces all communities. Therefore, the current study is an attempt to discover cyberbullying with its types found in one type of electronic communication, “Facebook”. The data are as type of screenshots and collected from an archived formal page on Facebook called “BBC News”. The data of the study encompass (10 comments) samples “screen shots” from different posts on “BBC News”. The analyses reveal “four” different types of cyberbullying which are employed in the data. The types are flaming, which is a reply directed towards other people’s comments; rumour spreading which is directed towards the posts or the channel; trolling, which is directed towards a specific post or the topic of discussion; and tagging, which occurs by making tags to other people with their usernames. Thus, cyberspace creates new different social environments that allow different online users from all over the world to contribute to electronic communication and cause many forms of cyberbullying.
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Wang, Yan, Feng Qing, and Ming Yan. "Dynamics of 2SIH2R Rumor-Spreading Model in a Heterogeneous Network." Wireless Communications and Mobile Computing 2022 (January 17, 2022): 1–13. http://dx.doi.org/10.1155/2022/7398387.
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Due to the development of social media, the threshold for information dissemination has become lower than ever before. As a special kind of information, rumors are usually harmful and are usually accompanied by a high degree of ambiguity that makes them difficult to immediately identify, but “rumors stop at wise men.” When someone identifies a rumor as false and begins spreading the truth instead, a confrontational relationship obtains between the rumor and the truth that leads to the stifling of the former. Given this, we developed a 2SIH2R model in this study that contains mechanisms of discernment and confrontation in a heterogeneous network to examine the dissemination of the rumor and the truth. By using mean-field equations of the 2SIH2R model, the threshold of the spreading of each can be determined separately in three cases. The results of a numerical simulation show that under the same conditions, the greater is the mechanism of discernment or confrontation, the smaller is the instantaneous maximum influence and the final range of influence of the rumor. It can be also concluded that the earlier release of the truth about the event by the government can significantly control the rumor. Secondly, it is more effective to publish the truth in advance than after the rumor has appeared. Thirdly, it is more important for the government to increase education and improve the ability of citizens to reveal the rumor than to increase the spread of the truth after the rumor occurs. These results can be used to help reduce the harmful effects of rumors.
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Li, Jinxian, Yanping Hu, and Zhen Jin. "Rumor Spreading of an SIHR Model in Heterogeneous Networks Based on Probability Generating Function." Complexity 2019 (June 23, 2019): 1–15. http://dx.doi.org/10.1155/2019/4268393.
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This paper focuses on the modeling of a rumor spreading in heterogeneous networks. Using the probability generating function method and pair approximation method, the current research obtains nonlinear differential equations to describe the dynamics of rumor spreading. The comparison between numerical simulations and Monte Carlo simulations confirms the accuracy of our model. Furthermore, the threshold condition is also obtained in this paper. The numerical simulation results show that the heterogeneity of the network accelerates the outbreak of rumors but reduces the maximum density of spreader and the scale of rumors. The present study also examines the effects of parameters on rumor transmission and the differences between rumor transmission recovery mechanisms and disease transmission recovery mechanisms.
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Bian, Tian, Xi Xiao, Tingyang Xu, Peilin Zhao, Wenbing Huang, Yu Rong, and Junzhou Huang. "Rumor Detection on Social Media with Bi-Directional Graph Convolutional Networks." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 01 (April 3, 2020): 549–56. http://dx.doi.org/10.1609/aaai.v34i01.5393.
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Social media has been developing rapidly in public due to its nature of spreading new information, which leads to rumors being circulated. Meanwhile, detecting rumors from such massive information in social media is becoming an arduous challenge. Therefore, some deep learning methods are applied to discover rumors through the way they spread, such as Recursive Neural Network (RvNN) and so on. However, these deep learning methods only take into account the patterns of deep propagation but ignore the structures of wide dispersion in rumor detection. Actually, propagation and dispersion are two crucial characteristics of rumors. In this paper, we propose a novel bi-directional graph model, named Bi-Directional Graph Convolutional Networks (Bi-GCN), to explore both characteristics by operating on both top-down and bottom-up propagation of rumors. It leverages a GCN with a top-down directed graph of rumor spreading to learn the patterns of rumor propagation; and a GCN with an opposite directed graph of rumor diffusion to capture the structures of rumor dispersion. Moreover, the information from source post is involved in each layer of GCN to enhance the influences from the roots of rumors. Encouraging empirical results on several benchmarks confirm the superiority of the proposed method over the state-of-the-art approaches.
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Wang, Yan, Feng Qing, and Lei Wang. "Rumor Dynamic Model considering Intentional Spreaders in Social Network." Discrete Dynamics in Nature and Society 2022 (February 26, 2022): 1–10. http://dx.doi.org/10.1155/2022/6044099.
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The development of network technology has created various platforms and methods for information dissemination. When rumors spread in social networks, they will rapidly spread and may cause social harm. Also, there are groups in social networks that create and spread rumors for the purpose of profit, thus expanding the scope of rumors. Therefore, based on the theory of complex network propagation dynamics, the study of the propagation law of rumors and the design of effective prevention and control strategies is of practical importance and theoretical significance for understanding the propagation laws of rumors and controlling the outbreak of rumors. The spreading process of rumors on social network platforms is focused here. The intentional spreader based on the classic rumor-spreading model is introduced. First, 2SIR rumor-spreading models on homogeneous and heterogeneous networks are established, respectively. Second, the steady-state analysis was separately carried out, and the corresponding propagation critical value was obtained: in the homogeneous network, the condition for the large-scale spread of rumors is α > m / k ¯ or β > δ / k ¯ ; in the heterogeneous network, the condition for the large-scale spread of rumors is α > m k ¯ / k 2 ¯ or β > δ k ¯ / k 2 ¯ . Finally, the simulation calculation and model feasibility verification were carried out on the model. The results show that the theoretical propagation threshold corresponds with the simulation results. According to the simulation results, the final influence of rumors has significantly decreased with decreasing values of β (intentional spreading rate) instead of α (unintentional spreading rate). It can be concluded that in the real-life rumor control process, more resources need to be invested in reducing the rate of intentional transmission instead of being indiscriminately put on controlling all spreaders of rumors.
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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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Huang, Da-Wen, Lu-Xing Yang, Xiaofan Yang, Yuan Yan Tang, and Jichao Bi. "Defending against Online Social Network Rumors through Optimal Control Approach." Discrete Dynamics in Nature and Society 2020 (September 30, 2020): 1–13. http://dx.doi.org/10.1155/2020/6263748.
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Rumors have been widely spread in online social networks and they become a major concern in modern society. This paper is devoted to the design of a cost-effective rumor-containing scheme in online social networks through an optimal control approach. First, a new individual-based rumor spreading model is proposed, and the model considers the influence of the external environment on rumor spreading for the first time. Second, the cost-effectiveness is recommended to balance the loss caused by rumors against the cost of a rumor-containing scheme. On this basis, we reduce the original problem to an optimal control model. Next, we prove that this model is solvable, and we present the optimality system for the model. Finally, we show that the resulting rumor-containing scheme is cost-effective through extensive computer experiments.
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Putri, Arrival Rince, Muthiah As Saidah, and Mahdhivan Syafwan. "DYNAMICS OF THE RUMOR SPREADING MODEL OF INDONESIA TWITTER CASE." BAREKENG: Jurnal Ilmu Matematika dan Terapan 16, no. 2 (June 1, 2022): 625–34. http://dx.doi.org/10.30598/barekengvol16iss2pp625-634.
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The study of the spreading of a rumor is significantly important to obtain scientific information and better strategies in reducing its negative impact. Twitter has become a medium for spreading rumors or hoaxes spatially and chronologically because it has a unique community structure. This study demonstrates the model of spreading rumors by considering credibility, correlation, and mass classification based on personality is discussed. The behavior of a model solution around equilibrium points is investigated with the Jacobian matrices. The stability also corresponds to a threshold number indicating the rumor fades away or continues to spread in the population. The analytical results are confirmed by actual data from Twitter in Indonesia with #SahkanRUUPKS. The simulation results show that the free rumor equilibrium point is stable and the threshold number is less than 1. Our study shows that the number of spreaders does not increase and the #SahkanRUUPKS rumor will vanish.
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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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Yu, Shuzhen, Zhiyong Yu, and Haijun Jiang. "Stability, Hopf Bifurcation and Optimal Control of Multilingual Rumor-Spreading Model with Isolation Mechanism." Mathematics 10, no. 23 (December 1, 2022): 4556. http://dx.doi.org/10.3390/math10234556.
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The propagation of rumors on online social networks (OSNs) brings an awful lot of trouble to people’s life and society. Aiming at combating rumors spreading on OSNs, two novel rumor-propagation models without and with time delays are proposed, which combine with the influence of the immune mechanism, isolation mechanism and network structure. Firstly, we analyze the existence of rumor equilibria and obtain some existence conditions of backward bifurcation. Secondly, the local stabilities of rumor-free and rumor equilibria are proved by using the Jacobian matrix method, and some critical conditions for the existence of Hopf bifurcation are acquired by selecting critical parameters and delays as bifurcation parameters. Furthermore, an optimal control method is proposed, which can prevent the spread of rumors within an expected time period and minimize the cost of control. Finally, some numerical simulations are provided to verify the effectiveness of the proposed theoretical results.
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Angali, Adel, Musa Mojarad, and Hassan Arfaeinia. "ILSHR Rumor Spreading Model by Combining SIHR and ILSR Models in Complex Networks." International Journal of Intelligent Systems and Applications 13, no. 6 (December 8, 2021): 51–59. http://dx.doi.org/10.5815/ijisa.2021.06.05.
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Rumor is an important form of social interaction. However, spreading harmful rumors can have a significant negative impact on social welfare. Therefore, it is important to examine rumor models. Rumors are often defined as unconfirmed details or descriptions of public things, events, or issues that are made and promoted through various tools. In this paper, the Ignorant-Lurker-Spreader-Hibernator-Removal (ILSHR) rumor spreading model has been developed by combining the ILSR and SIHR epidemic models. In addition to the characteristics of the lurker group of ILSR, this model also considers the characteristics of the hibernator group of the SIHR model. Due to the complexity of the complex network structure, the state transition function for each node is defined based on their degree to make the proposed model more efficient. Numerical simulations have been performed to compare the ILSHR rumor spreading model with other similar models on the Sina Weibo dataset. The results show more effective ILSHR performance with 95.83% accuracy than CSRT and SIR-IM models.
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Luo, Yongcong, and Jing Ma. "The influence of positive news on rumor spreading in social networks with scale-free characteristics." International Journal of Modern Physics C 29, no. 09 (September 2018): 1850078. http://dx.doi.org/10.1142/s012918311850078x.
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We explore the impact of positive news on rumor spreading in this paper. It is a fact that most of the rumors related to hot events or emergencies can be propagated rapidly on the hotbed of online social networks. In Chinese words, it is better to divert rather than block. Therefore, we propose the spreading model [Formula: see text] in which positive news is a good factor to guide rumor spreading. Based on transition probability method, we have got the spreading parameters of the [Formula: see text] model by running the rumor spreading process in online social networks with scale-free characteristics. The results give a good proof that improving the activity of the positive news spreader [Formula: see text] derived from the [Formula: see text] model can guide and restrain the spreading speed of rumor smoothly.
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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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LANDER, JAMES. "A TALE OF TWO HOAXES IN BRITAIN AND FRANCE IN 1775." Historical Journal 49, no. 4 (November 24, 2006): 995–1024. http://dx.doi.org/10.1017/s0018246x06005711.
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In October 1775 two hoaxes, perpetrated for separate reasons by John Wilkes and his friend, the Chevalier d’Eon, briefly collided. Wilkes’s hoax, the ‘Sayre plot’, was probably intended to provoke a test of the constitutionality of the recent ‘King’s Proclamation’, which encroached upon the statutory definition of treason. The hoax involved creating the impression that a conspiracy existed to resolve the deepening American crisis by overthrowing George III. D’Eon’s hoax involved spreading the rumour that he himself was a woman in order to embarrass the French king into recalling him from exile on d’Eon’s terms, including a generous financial package. For Wilkes, although neither George III’s overthrow nor the modification of his colonial policy were likely expectations, either result would have been a bonus. And although d’Eon was unquestionably a man, he did actually (if inexplicably) desire to be perceived as a woman living the life of an heroic man. When d’Eon’s hoax suddenly progressed too far – trapping him into agreeing to dress as a woman, which, at first, he seemed unwilling to do – he delayed signing the deal for a month, until he saw that the ‘Sayre plot’ (whose success could have strengthened d’Eon’s negotiating position) had utterly failed.
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Zhang, Yi, Jiuping Xu, and Yue Wu. "A fuzzy rumor spreading model based on transmission capacity." International Journal of Modern Physics C 29, no. 02 (February 2018): 1850012. http://dx.doi.org/10.1142/s0129183118500122.
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This paper proposes a rumor spreading model that considers three main factors: the event importance, event ambiguity, and the publics critical sense, each of which are defined by decision makers using linguistic descriptions and then transformed into triangular fuzzy numbers. To calculate the resultant force of these three factors, the transmission capacity and a new parameter category with fuzzy variables are determined. A rumor spreading model is then proposed which has fuzzy parameters rather than the fixed parameters in traditional models. As the proposed model considers the comprehensive factors affecting rumors from three aspects rather than examining special factors from a particular aspect. The proposed rumor spreading model is tested using different parameters for several different conditions on BA networks and three special cases are simulated. The simulation results for all three cases suggested that events of low importance, those that are only clarifying facts, and those that are strongly critical do not result in rumors. Therefore, the model assessment results were proven to be in agreement with reality. Parameters for the model were then determined and applied to an analysis of the 7.23 Yong–Wen line major transportation accident (YWMTA). When the simulated data were compared with the real data from this accident, the results demonstrated that the interval for the rumor spreading key point in the model was accurate, and that the key point for the YWMTA rumor spread fell into the range estimated by the model.
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Zhao, Xiaxia, and Jianzhong Wang. "Dynamical Model about Rumor Spreading with Medium." Discrete Dynamics in Nature and Society 2013 (2013): 1–9. http://dx.doi.org/10.1155/2013/586867.
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Rumor is a kind of social remark, that is untrue, and not be confirmed, and spreads on a large scale in a short time. Usually, it can induce a cloud of pressure, anxiety, and panic. Traditionally, it is propagated by word of mouth. Nowadays, with the emergence of the internet, rumors can be spread by instant messengers, emails, or publishing. With this new pattern of spreading, anISRWdynamical model considering the medium as a subclass is established. Beside the dynamical analysis of the model, we mainly explore the mechanism of spreading of individuals-to-individuals and medium-to-individual. By numerical simulation, we find that if we want to control the rumor spreading, it will not only need to control the rate of change of the spreader subclass, but also need to control the change of the information about rumor in medium which has larger influence. Moreover, to control the effusion of rumor is more important than deleting existing information about rumor. On the one hand, government should enhance the management of internet. On the other hand, relevant legal institutions for punishing the rumor creator and spreader on internet who can be tracked should be established. Using this way, involved authorities can propose efficient measures to control the rumor spreading to keep the stabilization of society and development of economy.
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Wei, Yanhui, Liang’an Huo, and Hongguang He. "Research on Rumor-Spreading Model with Holling Type III Functional Response." Mathematics 10, no. 4 (February 18, 2022): 632. http://dx.doi.org/10.3390/math10040632.
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In this paper, a rumor-spreading model with Holling type III functional response was established. The existence of the equilibrium points was discussed. According to the Routh–Hurwitz criteria, the locally asymptotic stability of the equilibrium points was analyzed. The global stability of the equilibrium points was proven based on Lasalle’s invariance principle and generalized Bendixson–Dulac theorem. Numerical simulations were carried out to illustrate the impact of different parameters on the spread of rumors. When the stifling rate λ increases, or the predation capacity β or the system coming rate k decreases, the number of rumor-spreaders is reduced to extinction. The results provide theory, method and decision support for effectively controlling the spread of rumors.
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Wu, Pinmo, Xiaowen Qu, and Zhuoxi Zhong. "How Collective Intelligence Restrains the Rumor Spreading in Emergencies?" BCP Social Sciences & Humanities 16 (March 26, 2022): 145–52. http://dx.doi.org/10.54691/bcpssh.v16i.452.
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When communicating online under COVID-19 epidemic in 2020, all kinds of rumors are widely spread on the Internet. Coming with the spread of virus, the rumor spreading not only threaten the public health, but also facilitate panic and destroy the harmony of society. This study took the COVID-19 epidemic, a serious public health emergency, as an example. Firstly, we build up a Structural Equation Modeling (SEM) containing the influential factors of Collective Intelligence on unconfirmed information dissemination (UID) on social media, and then conduct an empirical test based on the survey data. The results show that the use of Collective Intelligence can restrain the spread of rumor in public health emergencies, among which critical thinking, collective refutation and proof, crowdsourcing and member heterogeneity are the main restraining factors. However, opinion leaders would facilitate the spread of rumor. This paper not only enriches the theory of Collective Intelligence and rumor management, but also has important practical significance for suppressing rumor spreading during the emergencies.
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Xu, Jiuping, and Yi Zhang. "Event ambiguity fuels the effective spread of rumors." International Journal of Modern Physics C 26, no. 03 (February 25, 2015): 1550033. http://dx.doi.org/10.1142/s0129183115500333.
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In this paper, a new rumor spreading model which quantifies a specific rumor spreading feature is proposed. The specific feature focused on is the important role the event ambiguity plays in the rumor spreading process. To study the impact of this event ambiguity on the spread of rumors, the probability p(t) that an individual becomes a rumor spreader from an initially unaware person at time t is built. p(t) reflects the extent of event ambiguity, and a parameter c of p(t) is used to measure the speed at which the event moves from ambiguity to confirmation. At the same time, a principle is given to decide on the correct value for parameter c A rumor spreading model is then developed with this function added as a parameter to the traditional model. Then, several rumor spreading model simulations are conducted with different values for c on both regular networks and ER random networks. The simulation results indicate that a rumor spreads faster and more broadly when c is smaller. This shows that if events are ambiguous over a longer time, rumor spreading appears to be more effective, and is influenced more significantly by parameter c in a random network than in a regular network. We then determine parameters of this model through data fitting of the missing Malaysian plane, and apply this model to an analysis of the missing Malaysian plane. The simulation results demonstrate that the most critical time for authorities to control rumor spreading is in the early stages of a critical event.
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Zhang, Wei, Hongyong Deng, Xingmei Li, and Huan Liu. "Dynamics of the Rumor-Spreading Model with Control Mechanism in Complex Network." Journal of Mathematics 2022 (January 12, 2022): 1–17. http://dx.doi.org/10.1155/2022/5700374.
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The spread of rumors has a great impact on social order, people’s psychology, and life. In recent years, the application of rumor-spreading models in complex networks has received extensive attention. Taking the management and control of rumors by relevant departments in real life into account, the SIDRQ rumor-spreading model that combines forgetting mechanism, immune mechanism, and suspicion mechanism and guides on a uniform network is established in this paper. Then, the basic reproductive number of the system and the unique existence of the solution are discussed, and the stability of the system is analyzed using the basic reproductive number, Lyapunov function, and Lienard and Chipart theorem; furthermore, the basic reproductive number may not be able to deduce the stability of the system and a counterexample is given. Finally, the influence of different parameters on the spread of rumors is studied, and the validity of the theoretical results is verified.
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Jing, Wang, Li Min, Wang Ya-Qi, Zhou Zi-Chen, and Zhang Li-Qiong. "The influence of oblivion-recall mechanism and loss-interest mechanism on the spread of rumors in complex networks." International Journal of Modern Physics C 30, no. 09 (September 2019): 1950075. http://dx.doi.org/10.1142/s012918311950075x.
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Studying more realistic propagation mechanisms of rumors is crucial to controlling their spreading. Considering the reality of people’s forgetting and losing interest in the process of rumor spreading, the oblivion-recall mechanism and the loss-interest mechanism are both introduced in this paper to construct a novel susceptible-infected-removed (SIR) model. In our SIR model, the forgetting is regarded as an independent state type of the population, and we use the forgetting factor [Formula: see text] and the recall factor [Formula: see text] to characterize the oblivion-recall mechanism. The mean-field equations are established respectively to describe the transmission dynamics of rumors in homogeneous networks and inhomogeneous networks. By performing stable state analysis, the relationship between these two parameters [Formula: see text], [Formula: see text] and the propagation critical thresholds [Formula: see text] is investigated. It shows that [Formula: see text] is directly proportional to [Formula: see text], which indicates that the loss-interest mechanism makes [Formula: see text] exist, and the oblivion-recall mechanism increases the value of [Formula: see text]. Thus, the oblivion-recall mechanism reduces the outbreak probability of rumor spreading. It also reveals that when considering the impact of oblivion-recall mechanism, both the final rumor size and the propagation velocity of rumors decrease. Moreover, in the case of considering the existence of oblivion-recall mechanism, it is still found that the network topology is an important factor affecting the spread of rumors. We wish that our study can offer a new angle of view on the issue of the spread of rumors.
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Yue, Xuefeng, and Liangan Huo. "Analysis of the Stability and Optimal Control Strategy for an ISCR Rumor Propagation Model with Saturated Incidence and Time Delay on a Scale-Free Network." Mathematics 10, no. 20 (October 20, 2022): 3900. http://dx.doi.org/10.3390/math10203900.
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The spread of rumors in the era of new media poses a serious challenge to sustaining social order. Models regarding rumor propagation should be proposed in order to prevent them. Taking the cooling-off period into account in this paper, a modified ISCR model with saturated incidence and time delay on a scale-free network is introduced. The basic reproduction number R0, which does not depend on time delay τ, is given by simple calculation. The stability of the rumor-free and rumor-endemic equilibrium points is proved by constructing proper Lyapunov functions. The study of the ISCR rumor-spreading process acquires an understanding of the impact of many factors on the prevalence of rumors. Then, the optimal control strategy for restraining rumors is studied. Numerous sensitivity studies and numerical simulations are carried out. Based on the saturated incidence and time delay, results indicate that the effect of time delay plays a significant part in rumor propagation on a scale-free network.