Relevant bibliographies by topics / Rumour Spreading

Academic literature on the topic 'Rumour Spreading'

Author: Grafiati
Published: 10 December 2022
Last updated: 28 January 2023

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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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Dissertations / Theses on the topic "Rumour Spreading"

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Vera, Azócar Alberto Abel. "Adaptive rumor spreading." Tesis, Universidad de Chile, 2015. http://repositorio.uchile.cl/handle/2250/134778.

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Magíster en Gestión de Operaciones
Ingeniero Civil Industrial
El esparcimiento de rumores es un modelo intuitivo para la difusión de información en una red social. Una entidad que controla la red, por ejemplo el proveedor del servicio, desea acelerar el proceso de esparcimiento del rumor, de forma tal que se maximice la cantidad de información entregada. Este problema, definido a grandes rasgos, ha sido objeto de múltiples investigaciones en el último tiempo, entre otros como marketing viral y maximización de influencia. Un enfoque natural y ausente en los estudios previos es la adaptividad. En este trabajo se abordan las siguientes preguntas: ¿cómo el controlador puede usar la información del estado de la red para acelerar el proceso de rumor? y ¿cuánto beneficio se obtiene de tal conocimiento? Un concepto novedoso es la comunicación oportunista en redes; cada agente de la red social comparte información (noticias, actualización de software, etc.) con otros usuarios al momento de estar momentáneamente en rango (vía wi-fi, bluetooth, etc.), de esta forma se evita la saturación de la infraestructura que soporta la red. Con esta motivación se estudia un modelo a tiempo continuo, donde cada par de nodos se comunica de acuerdo a un proceso de Poisson de cierta tasa y el rumor se transmite siempre que alguno estuviera informado. Las anteriores comunicaciones no tienen costo para el controlador, pero si éste lo desea puede informar a cualquier nodo pagando un costo unitario por ello. En vez de la usual restricción de presupuesto se fija un deadline, en tal tiempo todos los nodos deben estar informados, debiendo pagar el controlador un costo unitario por cada nodo que no haya obtenido el rumor antes del deadline. Una estrategia no-adaptativa puede informar sólo al comienzo del periodo y cuando se cumple el deadline, pagando por todos aquellos nodos que no se comunicaron nunca con otro nodo informado. Una estrategia adaptativa puede intervenir la red en cualquier instante, usando toda la información disponible hasta ese entonces, en particular sabiendo cuales nodos tienen el rumor en cada momento. El resultado principal de este trabajo es que en el caso homogéneo, donde cada par de nodos se encuentra con la misma tasa, el beneficio de la adaptividad está acotado por una constante. La demostración requiere un entendimiento profundo del proceso estocástico que domina el sistema, que se cree ya una contribución interesante. Adicionalmente, se presenta una extensión natural del caso homogéneo, donde el controlador está interesado sólo en un conjunto de nodos y no en toda la red social, se demuestra que en este escenario el beneficio de la adaptividad también está acotado por una constante. Finalmente, se muestra que, sin el supuesto de homogeneidad, el beneficio de la adaptividad puede crecer de forma no acotada.
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Fouz, Mahmoud [Verfasser], and Benjamin [Akademischer Betreuer] Doerr. "Randomized rumor spreading in social networks and complete graphs / Mahmoud Fouz. Betreuer: Benjamin Doerr." Saarbrücken : Saarländische Universitäts- und Landesbibliothek, 2012. http://d-nb.info/1052549861/34.

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Kostrygin, Anatolii. "Precise Analysis of Epidemic Algorithms." Thesis, Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLX042/document.

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La dissémination collaborative d'une information d'un agent à tous les autres agents d'un système distribué est un problème fondamental qui est particulièrement important lorsque l'on veut obtenir des algorithmes distribués qui sont à la fois robustes et fonctionnent dans un cadre anonyme, c'est-à-dire sans supposer que les agents possèdent des identifiants distincts connus. Ce problème, connu sous le nom de problème de propagation de rumeur , est à la base de nombreux algorithmes de communication sur des réseaux de capteurs sans-fil [Dimakis et al. (2010)] ou des réseaux mobiles ad-hoc. Il est aussi une brique de base centrale pour de nombreux algorithmes distribués avancés [Mosk-Aoyama et Shah (2008)].Les méthodes les plus connues pour surmonter les défis de robustesse et d'anonymat sont les algorithmes basés sur les ragots ( gossip-based algorithms ), c'est-à-dire sur la paradigme que les agents contact aléatoirement les autres agents pour envoyer ou récupérer l'information. Nousproposons une méthode générale d'analyse de la performance des algorithmes basés sur les ragots dans les graphes complets. Contrairement aux résultats précédents basés sur la structure précise des processus étudiés, notre analyse est basée sur la probabilité et la covariance des évènements correspondants au fait qu'un agent non-informé s'informe. Cette universalité nous permet de reproduire les résultats basiques concernant les protocoles classiques de push, pull et push-pull ainsi qu'analyser les certaines variantions telles que les échecs de communications ou les communications simultanés multiples réalisées par chaque agent. De plus, nous sommescapables d'analyser les certains modèles dynamiques quand le réseaux forme un graphe aléatoire échantillonné à nouveau à chaque étape [Clementi et al. (ESA 2013)]. Malgré sa généralité, notre méthode est simple et précise. Elle nous permet de déterminer l'espérance du temps de la diffusion à une constante additive près, ce qu'il est plus précis que la plupart des résultatsprécédents. Nous montrons aussi que la déviation du temps de la diffusion par rapport à son espérance est inférieure d'une constante r avec la probabilité au moins 1 − exp(Ω(r)).À la fin, nous discutons d'une hypothèse classique que les agents peuvent répondre à plusieurs appels entrants. Nous observons que la restriction à un seul appel entrant par agent provoque une décélération importante du temps de la diffusion pour un protocole de push-pull. En particulier, une phase finale du processus prend le temps logarithmique au lieu du temps double logarithmique. De plus, cela augmente le nombre de messages passés de Θ(n log log n) (valeur optimale selon [Karp et al. (FOCS 2000)]) au Θ(n log n) . Nous proposons une variation simple du protocole de push-pull qui rétablit une phase double logarithmique à nouveau et donc le nombre de messages passés redescend sur sa valeur optimal
Epidemic algorithms are distributed algorithms in which the agents in thenetwork involve peers similarly to the spread of epidemics. In this work, we focus on randomized rumor spreading -- a class of epidemic algorithms based on the paradigm that nodes call random neighbors and exchange information with these contacts. Randomized rumor spreading has found numerous applications from the consistency maintenance of replicated databases to newsspreading in social networks. Numerous mathematical analyses of different rumor spreading algorithms can be found in the literature. Some of them provide extremely sharp estimates for the performance of such processes, but most of them are based on the inherent properties of concrete algorithms.We develop new simple and generic method to analyze randomized rumor spreading processes in fully connected networks. In contrast to all previous works, which heavily exploit the precise definition of the process under investigation, we only need to understand the probability and the covariance of the events that uninformed nodes become informed. This universality allows us to easily analyze the classic push, pull, and push-pull protocols both in their pure version and in several variations such as when messages fail with constant probability or when nodes call a random number of others each round. Some dynamic models can be analyzed as well, e.g., when the network is a random graph sampled independently each round [Clementi et al. (ESA 2013)]. Despite this generality, our method determines the expected rumor spreading time precisely apart from additive constants, which is more precise than almost all previous works. We also prove tail bounds showing that a deviation from the expectation by more than an additive number of r rounds occurs with probability at most exp(−Ω(r)).We further use our method to discuss the common assumption that nodes can answer any number of incoming calls. We observe that the restriction that only one call can be answered leads to a significant increase of the runtime of the push-pull protocol. In particular, the double logarithmic end phase of the process now takes logarithmic time. This also increases the message complexity from the asymptotically optimal Θ(n log log n) [Karp, Shenker, Schindelhauer, Vöcking (FOCS 2000)] to Θ(n log n). We propose a simple variation of the push-pull protocol that reverts back to the double logarithmic end phase and thus to the Θ(n log log n) message complexity
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Oliveros, Didier Augusto Vega. "Dinâmicas de propagação de informações e rumores em redes sociais." Universidade de São Paulo, 2017. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-13092017-102818/.

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As redes sociais se tornaram um novo e importante meio de intercâmbio de informações, ideias e comunicação que aproximam parentes e amigos sem importar as distâncias. Dada a natureza aberta da Internet, as informações podem fluir muito fácil e rápido na população. A rede pode ser representada como um grafo, onde os indivíduos ou organizações são o conjunto de vértices e os relacionamentos ou conexões entre os vértices são o conjunto de arestas. Além disso, as redes sociais representam intrinsecamente a estrutura de um sistema mais complexo que é a sociedade. Estas estruturas estão relacionadas com as características dos indivíduos. Por exemplo, os indivíduos mais populares são aqueles com maior número de conexões. Em particular, é aceito que a estrutura da rede pode afetar a forma como a informação se propaga nas redes sociais. No entanto, ainda não está claro como a estrutura influencia na propagação, como medir seu impacto e quais as possíveis estratégias para controlar o processo de difusão. Nesta tese buscamos contribuir nas análises da interação entre as dinâmicas de propagação de informações e rumores e a estrutura da rede. Propomos um modelo de propagação mais realista considerando a heterogeneidade dos indivíduos na transmissão de ideias ou informações. Nós confirmamos a presença de propagadores mais influentes na dinâmica de rumor e observamos que é possível melhorar ou reduzir expressivamente a difusão de uma informação ao selecionar uma fração muito pequena de propagadores influentes. No caso em que se objetiva selecionar um conjunto de propagadores iniciais que maximizem a difusão de informação, a melhor opção é selecionar os indivíduos mais centrais ou importantes nas comunidades. Porém, se o padrão de conexão dos vértices está negativamente correlacionado, a melhor alternativa é escolher entre os indivíduos mais centrais de toda a rede. Por outro lado, através de abordagens topológicas e de técnicas de aprendizagem máquina, identificamos aos propagadores menos influentes e mostramos que eles atuam como um firewall no processo de difusão. Nós propomos um método adaptativo de reconexão entre os vértices menos influentes para um indivíduo central da rede, sem afetar a distribuição de grau da rede. Aplicando o nosso método em uma pequena fração de propagadores menos influentes, observamos um aumento importante na capacidade de propagação desses vértices e da rede toda. Nossos resultados vêm de uma ampla gama de simulações em conjuntos de dados artificiais e do mundo real e a comparação com modelos clássicos de propagação da literatura. A propagação da informação em redes é de grande relevância para as áreas de publicidade e marketing, educação, campanhas políticas ou de saúde, entre outras. Os resultados desta tese podem ser aplicados e estendidos em diferentes campos de pesquisa como redes biológicas e modelos de comportamento social animal, modelos de propagação de epidemias e na saúde pública, entre outros.
On-line Social networks become a new and important medium of exchange of information, ideas and communication that approximate relatives and friends no matter the distances. Given the open nature of the Internet, the information can flow very easy and fast in the population. The network can be represented as a graph, where individuals or organizations are the set of vertices and the relationship or connection among the vertices are the set of edge. Moreover, the social networks are also intrinsically representing the structure of a more complex system that is the society. These structures are related with characteristics of the subjects, like the most popular individuals have many connections, the correlation in the connectivity of vertices that is a trace of homophily phenomenon, among many others. In particular, it is well accepted that the structure of the network can affect the way the information propagates on the social networks. However, how the structure impacts in the propagation, how to measure that impact and what are the strategies for controlling the propagation of some information, it is still unclear. In this thesis, we seek to contribute in the analysis of the interplay between the dynamics of information and rumor spreading and the structure of the networks. We propose a more realistic propagation model considering the heterogeneity of the individuals in the transmission of ideas or information. We confirm the presence of influential spreaders in the rumor propagation process and found that selecting a very small fraction of influential spreaders, it is possible to expressively improve or reduce de diffusion of some information on the network. In the case we want to select a set of initial spreaders that maximize the information diffusion on the network, the simple and best alternative is to select the most central or important individuals from the networks communities. But, if the pattern of connection of the networks is negatively correlated, the best alternative is to choose from the most central individuals in the whole network. On the other hand, we identify, by topological approach and machine learning techniques, the least influential spreaders and show that they act as a firewall in the propagation process. We propose an adaptative method that rewires one edge for a given vertex to a central individual, without affecting the overall distribution of connection. Applying our proposed method in a little fraction of least influential spreaders, we observed an important increasing in the capacity of propagation of these vertices and in the overall network. Our results are from a wide range of simulations in artificial and real-world data sets and the comparison with the classical rumor propagation model. The propagation of information is of greatest relevance for publicity and marketing area, education, political or health campaigns, among others. The results of this these might be applicable and extended in different research fields like biological networks and animal social behavior models.
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Josefsson, Joakim, Jesper Jarl, and Mikael Lödöen. "Den kaotiska ryktesspridningen : En teorijämförelse av begreppet word of mouth och appliceringen av den utredda definitionen på Internetforumet Prisjakt.nu." Thesis, Jönköping University, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-1202.

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Dagens samhälle är präglat av ett enormt reklamutbud och reklamstrategier. I denna djungel av marknadsföring har företag ibland valt en annan strategi, en relativt outnyttjad strategi, som baseras på rykten om produkten, tjänsten eller företaget och är det som används som marknadsföring. Denna strategi kallas för word of mouth. Ena syftet har varit att undersöka hur word of mouth definieras av olika författare. Genom att göra en jämförelse av teorier av begreppet word of mouth har ett försök gjorts att skapa en definition av begreppet, som tillämpas på vårt andra syfte med undersökningen. Det andra syftet är att undersöka om kommunikationen på det utvalda internetforum prisjakt.nu kan liknas vid vår definition av word of mouth. Genom vår undersökning ville vi exemplifiera vad word of mouth är och vilket som är dess användningsområde. Forskningen har därför genomförts genom en litteraturstudie där word of mouth som begrepp har kartlagts och förklarats. Genom litteraturstudien utvecklades sedan en jämförelse av teorier av begreppet word of mouth. Dessa jämförelser av begreppet gjorde det möjligt för oss att kunna applicera begreppet på det tidigare nämnda utvalda internetforum. När slutdefinitionen fanns tillhanda, utfördes studien på Internetforumet Prisjakt.nu, med inriktning på en produkt som det pratades mycket om på detta Internetforum. Denna produkt valdes strategiskt då vi ansåg att det var väsentligt för undersökningen att produkten ännu inte fanns på marknaden, då tidigare teorier om word of mouths beteende tydde på att frekvensen på kommunikation om produkten var som högst innan produkten släppts. Denna produkt var Apple Iphone, som då ännu inte lanserats i Sverige. Därefter genomfördes studien med vår definition av traditionell och generaliserad word of mouth som teoretisk utgångspunkt, och studien resulterade i att förekomsten var positiv för word of mouth-baserad kommunikation på internetforumet prisjakt.nu. Vår definition av begreppet word of mouth lyder så som följer: “Word of mouth är interpersonell kommunikation, där självgenererande ryktesspridning om personer, företag, produkter eller tjänster kan ske via telefon, Internet eller mun-till-mun-kommunikation”. Kommunikationen på det undersökta forumet innehåller en hög grad av interpersonell kommunikation, självgenererande ryktesspridning och har en kommersiell karaktär på dess kommunikation, och uppfyller således de tre delar som enligt vår definition behövs för att kalla det en word of mouth-baserad kommunikation.


Today’s society is characterized by an enormously large advertising range and commercial strategies. In this jungle of marketing companies often chosen another strategy, a comparatively unknown strategy based on rumors about a product, service or company as marketing. That strategy is called word of mouth. The purpose of examine word of mouth as concept is important, because today the concept is defined on various manner of several different authors. By making a theory comparison of the conception word of mouth it is possible to create a good definition of the concept, this because that the concept word of mouth lacks a definite definition, that can be applied on our second purpose. The second purpose is to examine if the communication on the selected internet forum prisjakt.nu is word of mouth. In earlier cases this would been examined according to electronic word of mouth that is an adjustment to the internet, but we felt that the concept almost was identical to other word of mouth-theories we choose to make a theory comparison of the concept as described above. Through our examination we wanted to exemplify what word of mouth is and what it can be used for. A literature study was done as a replacement for the earlier research, the earlier research missed an evident significance of the conception word of mouth, and it handled its usage. The research had therefore been made through a literature study where the concept has been plotted and explained. Through the literature study the theory comparison of the concept word of mouth developed. . The theory comparison made it possible for us to apply the concept on the earlier mentioned internet forum. When the finished definition was at hand, the study was made on the internet forum prisjakt.nu, with the concentration on a product that had a big talk about it on this internet forum. This product was strategically selected as we considered it as an essential part for the research as the product didn’t even exist on the market; this due to the earlier theory’s about word of mouths behaviour that indicated that the frequency of the communication about the product was highest just before the product was released in the USA. The product was the Apple Iphone, and has after this research not yet been released in Sweden.The result shows that our definition of word of mouth can be applied on internet forums and that a separate concept for word of mouth on the internet is unnecessary. Our definition of word of mouth is as follows: “Word of mouth is an interpersonal communication, where self generating rumour spreading about people, companies, products or services can be made via telephone, internet or by mouth-to-mouth-communication“. The communication on the studied forums contain a high pitch of interpersonal communication, self generating rumour spread and have a commercialized character on it’s communication and fulfil the three parts that according of our theory comparison is needed for being called word of mouth-based communication.

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6

Taghavianfar, Mohsen. "An Investigation on Network Entropy-Gossiping Protocol and Anti-entropy Evaluation." Thesis, Blekinge Tekniska Högskola, Sektionen för ingenjörsvetenskap, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-2684.

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This thesis is concerned with studying the behavior of a gossiping protocol in the specific sense meant by Ericsson; in the following pages I’ll introduce a Markov process which models the spread of information in such systems. The results will be verified by means of a discreet-event simulation.
Gossiping Protocols, are inherently random in behavior.Nonetheless, they are not structure-less. Their asymptotic behavior when implemented in large scales is the matter of focus in this thesis.
Tel: +46709700505 Address: Pinnharvsgatan 3 E lgh 1202 43147 Mölndal Sweden
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7

Huber, Anna [Verfasser]. "Randomized rounding and rumor spreading with stochastic dependencies / vorgelegt von Anna Huber." 2010. http://d-nb.info/1008296163/34.

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shih-chieh, Chang, and 張世杰. "A Study of the Securities Market Manipulation ─ focusing on spreading rumors and false information." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/26962716161365869789.

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碩士
南台科技大學
財經法律研究所
100
The goal of formulation of Securities and Exchange Act of Taiwan, R.O.C. is “develops the national economy” and “the safeguard investment”. One of the most important functions of Securities Exchange Market, lies in forms the moderate price. Article 155 of Securities Exchange Act, so called “anti-manipulation clause” is designed for this purpose.There are six kinds of manipulation in Article 155 of Securities Exchange Act. And this thesis focusing on spreading rumors and false information of paragraph1, subparagraph 6 of Article 155 of Securities Exchange Act. The Securities and Exchange Act of Taiwan, R.O.C., Section 155, is specifically made for this kind of market manipulation, so called “Anti-manipulation provision”. There are five types of manipulation in this specific term and this study will be focusing on “spreading rumors or false information” in the Securities and Exchange Act of Taiwan, R.O.C., Section 155, Provision 1, Article 6. Here we are going to understand every type of the manipulation then compare them with the legislation of the U.S. and Japan. In the end, analyzing the key factors and related problems concerning the application of the “Illegal price-fixing by spreading rumors or false information”, also identify the problems from the actual cases then make relevant amendment.
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9

Hsu, Chan-Jung, and 許展榕. "The study on the boundaries between press freedom and securities market manipulation — focusing on spreading rumors and false information." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/susd9p.

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碩士
銘傳大學
法律學系碩士班
97
The securities market is a prospective index of the economic development of a nation, the prosperity or depression of which would influence investors’ behavior. Securities, which are different from personal property and real estate, hold abstract and flexible values. Investors estimate the value of securities through factors such as corporate prospects, profitability, political and economic trend, and surrounding environment. This function could not be achieved if the market power is manipulated. As a result, manipulation should be prohibited. Article 155 of Securities Exchange Act, so called “anti-manipulation clause” is designed for this purpose.There are six kinds of manipulation in Article 155 of Securities Exchange Act. And this thesis focusing on spreading rumors and false information of paragraph1, subparagraph 6 of Article 155 of Securities Exchange Act. This thesis indicates that securities market manipulation and securities frauds are one object with two sides. It is very hard to definite the market manipulation. According to the principle of "nulla poena sine lege", the legislation of market manipulation must based on the theory of securities frauds. There are no any limits to the subject of the crime of spreading rumors or false information to manipulate prices. Spreading mean that seminate on uncertain peoples. False information means that inconsistent description of the truth. The discussion on the false information is always focused on the fraudulent financial statement. Rumors means the gossip which entirely groundless. The opinion of government officials is closed the life of general public on the discussion of the rumor.Besides, the analyst recommendations of securities firms still be discussed which constitute the crime of spreading rumors or false information to manipulate prices. Mess media have penetration and influence on the modern society.Maybe it will be the subject of the crime of spreading rumors or false information to manipulate prices. This thesis indicates that mess media have the effect on the securities market in Taiwan. It can be the subject of the crime of spreading rumors or false information to manipulate prices.But it must find out the subjective wrongful intent of frauds on the perpetrator. This thesis investigates related issues on the basis of the crime of spreading rumors or false information to manipulate prices. Finally, this thesis analyzes the precondition and application of this crime and brings out advices about its modification.
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FAN, CHENG-JUI, and 范成瑞. "A Study of the Securities Fraud and the Securities Market Manipulation－focusing on the General Antifraud Provisions of securities exchange act and spreading rumors and false Information." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/snesfd.

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Books on the topic "Rumour Spreading"

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Cracking the Code: Spreading Rumors. Nelson Publishing & Marketing, 2012.

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Licate, Jennifer, and Suzanne Beaky. Why Is He Spreading Rumors about Me? Lulu Press, Inc., 2022.

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Licate, Jennifer. Why Is He Spreading Rumors about Me? Teacher and Counselor Activity Guide. Boys Town Press, 2022.

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Asseraf, Arthur. Electric News in Colonial Algeria. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198844044.001.0001.

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How do the things which connect us divide us at the same time? This book tells a different history of globalization by tracing how news circulated in a divided society: Algeria under French rule in the late nineteenth and early twentieth centuries. The years between 1881 and 1940 were those of maximum colonial power in North Africa, a period of intense technological revolution, global high imperialism, and the expansion of settler colonialism. Algerians became connected to international networks of news, and local people followed distant events with great interest. But once news reached Algeria, accounts of recent events often provoked conflict as they moved between different social groups. In a society split between its native majority and a substantial settler minority, distant wars led to riots. Circulation and polarization were two sides of the same coin. Looking at a range of sources in multiple languages across colonial society, this book offers a new understanding of what news is. News was a whole ecosystem in which new technologies such as the printing press, the telegraph, the cinema and the radio interacted with older media like songs, rumours, letters, and manuscripts. The French government watched anxiously over these developments, monitoring Algerians’ reactions to news through an extensive network of surveillance that often ended up spreading news rather than controlling its flow. By tracking what different people thought was new, this history of news helps us reconsider the relationship between time, media, and historical change.
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Book chapters on the topic "Rumour Spreading"

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Acan, Hüseyin, Andrea Collevecchio, Abbas Mehrabian, and Nick Wormald. "On the Push&Pull Protocol for Rumour Spreading." In Trends in Mathematics, 3–10. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-51753-7_1.

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Correa, José, Marcos Kiwi, Neil Olver, and Alberto Vera. "Adaptive Rumor Spreading." In Web and Internet Economics, 272–85. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-48995-6_20.

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Chierichetti, Flavio, Silvio Lattanzi, and Alessandro Panconesi. "Rumor Spreading in Social Networks." In Automata, Languages and Programming, 375–86. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02930-1_31.

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Doerr, Benjamin, and Mahmoud Fouz. "Asymptotically Optimal Randomized Rumor Spreading." In Automata, Languages and Programming, 502–13. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22012-8_40.

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Bronner, Stephen Eric. "Spreading the News: The Protocols Triumphant." In A Rumor about the Jews, 83–109. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-95396-0_5.

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Panagiotou, Konstantinos, and Leo Speidel. "Asynchronous Rumor Spreading on Random Graphs." In Algorithms and Computation, 424–34. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-45030-3_40.

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Panagiotou, Konstantinos, Ali Pourmiri, and Thomas Sauerwald. "Faster Rumor Spreading with Multiple Calls." In Algorithms and Computation, 446–56. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-45030-3_42.

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Daum, Sebastian, Fabian Kuhn, and Yannic Maus. "Rumor Spreading with Bounded In-Degree." In Structural Information and Communication Complexity, 323–39. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-48314-6_21.

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Clementi, Andrea, Pierluigi Crescenzi, Carola Doerr, Pierre Fraigniaud, Marco Isopi, Alessandro Panconesi, Francesco Pasquale, and Riccardo Silvestri. "Rumor Spreading in Random Evolving Graphs." In Lecture Notes in Computer Science, 325–36. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40450-4_28.

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Berenbrink, Petra, Robert Elsässer, and Thomas Sauerwald. "Communication Complexity of Quasirandom Rumor Spreading." In Algorithms – ESA 2010, 134–45. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15775-2_12.

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Conference papers on the topic "Rumour Spreading"

1

Chierichetti, Flavio, Silvio Lattanzi, and Alessandro Panconesi. "Rumour spreading and graph conductance." In Proceedings of the Twenty-First Annual ACM-SIAM Symposium on Discrete Algorithms. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2010. http://dx.doi.org/10.1137/1.9781611973075.135.

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Karelin, Vladimir V., Vladimir M. Bure, Lyudmila N. Polyakova, and Michail V. Svirkin. "A stochastic model of rumour spreading." In 2017 Constructive Nonsmooth Analysis and Related Topics (dedicated to the memory of V.F. Demyanov) (CNSA). IEEE, 2017. http://dx.doi.org/10.1109/cnsa.2017.7973968.

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Chierichetti, Flavio, Silvio Lattanzi, and Alessandro Panconesi. "Almost tight bounds for rumour spreading with conductance." In the 42nd ACM symposium. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1806689.1806745.

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Acan, Huseyin, Andrea Collevecchio, Abbas Mehrabian, and Nick Wormald. "On the Push&Pull Protocol for Rumour Spreading." In PODC '15: ACM Symposium on Principles of Distributed Computing. New York, NY, USA: ACM, 2015. http://dx.doi.org/10.1145/2767386.2767416.

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Wang, Ping, Yixia Hu, and Qiao Li. "The Trust-Building Process in the Social Media Environment of Rumour Spreading." In GROUP '20: The 2020 ACM International Conference on Supporting Group Work. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3323994.3369882.

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Collard, Martine, Philippe Collard, Laurent Brisson, and Erick Stattner. "Rumor Spreading Modeling." In ASONAM '15: Advances in Social Networks Analysis and Mining 2015. New York, NY, USA: ACM, 2015. http://dx.doi.org/10.1145/2808797.2809299.

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Brach, Paweł, Alessandro Epasto, Alessandro Panconesi, and Piotr Sankowski. "Spreading rumours without the network." In the second edition of the ACM conference. New York, New York, USA: ACM Press, 2014. http://dx.doi.org/10.1145/2660460.2660472.

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Giakkoupis, George, and Thomas Sauerwald. "Rumor Spreading and Vertex Expansion." In Proceedings of the Twenty-Third Annual ACM-SIAM Symposium on Discrete Algorithms. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2012. http://dx.doi.org/10.1137/1.9781611973099.129.

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Doerr, Benjamin, Philipp Fischbeck, Clemens Frahnow, Tobias Friedrich, Timo Kötzing, and Martin Schirneck. "Island models meet rumor spreading." In GECCO '17: Genetic and Evolutionary Computation Conference. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3071178.3071206.

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Kostkova, Patty, Vino Mano, Heidi J. Larson, and William S. Schulz. "Who is Spreading Rumours about Vaccines?" In DH '17: International Conference on Digital Health. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3079452.3079505.

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