Os modelos de Daley-Kendall e Maki-Thompson são os dois modelos estocásticos para difusão de rumores mais citados até o momento. Em ambos, uma população finita fechada e totalmente misturada é subdividida em três classes de indivíduos denominados ignorantes, informantes e contidos. Depois de um rumor ser introduzido na população, difunde-se através desta seguindo determinadas regras que dependem da classe à qual a pessoa que sabe do rumor pertence. Tanto a proporção final de indivíduos que nunca chegam a conhecer o rumor quanto o tempo que este demora em ser difundido são variáveis de interesse para os modelos propostos. As técnicas encontradas na literatura para estudar modelos de rumores são o princípio de difusão de constantes arbitrárias; argumentos de martingais; o método de funções geradoras e a análise de versões determinísticas do processo. Neste trabalho apresentamos uma alternativa para essas técnicas baseando-nos na teoria de cadeias de Markov "density dependent''. O uso desta nova abordagem nos permite apresentar resultados assintóticos para um modelo geral que tem como casos particulares os famosos modelos de Daley-Kendall e Maki-Thompson, além de variações de modelos de rumores apresentados na literatura recentemente.; Daley-Kendall and Maki-Thompson models are the two most cited stochastic models for the spread of rumours phenomena...
A circulação de rumores é um processo comunicacional, resultado de ações coletivas. O fenômeno é definido como um tipo de informação não confirmada que se propaga em rede e que circula com a intenção de ser tomada como verdadeira. Apesar de poder ser inofensivo, o rumor também pode ser prejudicial, gerando graves conseqüências quando se trata de uma informação falsa. Nesta condição, sua disseminação num corpo social pode ser motivo de preocupação, dependendo da rapidez com que ele é passado adiante e da dimensão alcançada. Com o advento da Internet, ícone das tecnologias digitais, o sujeito social, antes limitado por questões temporais ou geográficas, passa a se comunicar e a se relacionar com outros indivíduos de maneira potencializada. Facilitando a produção e a busca de informações tanto quanto a comunicação globalizada em alta velocidade, a rede também potencializa o processo e os efeitos dos rumores, agora denominados boatos virtuais. Conseqüentemente, a Internet torna-se o meio ideal para a rápida propagação de um grande número de informações falsas a um número muito maior de indivíduos em curto espaço de tempo. E, atualmente, além das características próprias da rede permitirem essa disseminação em alta velocidade...
In 2003 five northern Nigerian states boycotted the oral polio vaccine due to fears that it was unsafe. Though the international responses have been scrutinised in the literature, this paper argues that lessons still need to be learnt from the boycott: that the origins and continuation of the boycott were due to specific local factors. We focus mainly on Kano state, which initiated the boycotts and continued to reject immunisations for the longest period, to provide a focused analysis of the internal dynamics and complex multifaceted causes of the boycott. We argue that the delay in resolving the year-long boycott was largely due to the spread of rumours at local levels, which were intensified by the outspoken involvement of high-profile individuals whose views were misunderstood or underestimated. We use sociological concepts to analyse why these men gained influence amongst northern Nigerian communities. This study has implications on contemporary policy: refusals still challenge the Global Polio Eradication Initiative; and polio remains endemic to Nigeria (Nigeria accounted for over half of global cases in 2012). This paper sheds light on how this problem may be tackled with the ultimate aim of vaccinating more children and eradicating polio.
This Thesis expands on the current developments of the theory of stochastic diffusion processes of rumours. This is done by advancing the current mathematical characterisation of the solution to the Daley-Kendall model of the simple S-I-R rumour to a physical solution of the sub-population distribution over time of the generalised simple stochastic spreading process in social situations. After discussing stochastic spreading processes in social situations such as the simple epidemic, the simple rumour, the spread of innovations and ad hoc communications networks, it uses the three sub-population simple rumour to develop the theory for the identification of the exact sub-population distribution over time. This is done by identifying the generalised form of the Laplace Transform Characterisation of the solution to the three sub-population single rumour process and the inverse Laplace Transform of this characterisation. In this discussion the concept of the Inter-Changeability Principle is introduced. The general theory is validated for the three population Daley-Kendall Rumour Model and results for the three, five and seven population Daley-Kendall Rumour Models are pre- sented and discussed. The α - p model results for pseudo-Maki-Thompson Models are presented and discussed. In subsequent discussion it presents for the first time a statement of the Threshold Problem for Stochastic Spreading Processes in Social settings as well as stating the associated Threshold Theorem. It also investigates limiting conditions.
Aspects of future research resulting from the extension of the three subpopulation model to more than three subpopulations are discussed at the end of the thesis. The computational demands of applying the theory to more than three subpopulations are restrictive; the size of the total population that can be considered at one time is considerably reduced. To retain the ability to compute a large population size...
Fonte: Instituto Universitário EuropeuPublicador: Instituto Universitário Europeu
Tipo: Tese de Doutorado
Relevância na Pesquisa
The liberation of Western Europe from Nazism meant the freeing of a high number of foreign citizens and soldiers. Many among them had been brought here for the purpose of (forced) labour in the Nazi war economy. In March 1945, 245,730 displaced persons (DPs) were counted in occupied Germany, of which 45,587 were Soviet citizens.1 The Soviet Union, like the other countries involved, expressed early on their wish to repatriate their own citizens. The repatriations were agreed upon in Yalta (February 1945) and were taking place at a large scale from May 1945 onward. As a result, by December 1945 the refugee organization at that time (the United Nations Relief and Rehabilitation Administration or UNRRA) had 21,435 Soviet citizens under its care, a number that had decreased to 6,770 in June 1947.2 Whereas the Allied initially predicted that repatriation would reach 98%, this expectation was completely crushed by the end of 1945. It started to sink in that the Soviet citizens still remaining in Western Europe at that time did not intend to return home.3 In general, their reluctance was motivated by fear for what might happen to them upon their return. In certain cases, the Soviet DPs (especially among the prisoners of war) had fought with the Nazi troops...
As breaking news unfolds people increasingly rely on social media to stay
abreast of the latest updates. The use of social media in such situations comes
with the caveat that new information being released piecemeal may encourage
rumours, many of which remain unverified long after their point of release.
Little is known, however, about the dynamics of the life cycle of a social
media rumour. In this paper we present a methodology that has enabled us to
collect, identify and annotate a dataset of 330 rumour threads (4,842 tweets)
associated with 9 newsworthy events. We analyse this dataset to understand how
users spread, support, or deny rumours that are later proven true or false, by
distinguishing two levels of status in a rumour life cycle i.e., before and
after its veracity status is resolved. The identification of rumours associated
with each event, as well as the tweet that resolved each rumour as true or
false, was performed by a team of journalists who tracked the events in real
time. Our study shows that rumours that are ultimately proven true tend to be
resolved faster than those that turn out to be false. Whilst one can readily
see users denying rumours once they have been debunked, users appear to be less
capable of distinguishing true from false rumours when their veracity remains
in question. In fact...
The spread of false rumours during emergencies can jeopardise the well-being
of citizens as they are monitoring the stream of news from social media to stay
abreast of the latest updates. In this paper, we describe the methodology we
have developed within the PHEME project for the collection and sampling of
conversational threads, as well as the tool we have developed to facilitate the
annotation of these threads so as to identify rumourous ones. We describe the
annotation task conducted on threads collected during the 2014 Ferguson unrest
and we present and analyse our findings. Our results show that we can collect
effectively social media rumours and identify multiple rumours associated with
a range of stories that would have been hard to identify by relying on existing
techniques that need manual input of rumour-specific keywords.
We introduce a general stochastic model for the spread of rumours, and derive
mean-field equations that describe the dynamics of the model on complex social
networks (in particular those mediated by the Internet). We use analytical and
numerical solutions of these equations to examine the threshold behavior and
dynamics of the model on several models of such networks: random graphs,
uncorrelated scale-free networks and scale-free networks with assortative
degree correlations. We show that in both homogeneous networks and random
graphs the model exhibits a critical threshold in the rumour spreading rate
below which a rumour cannot propagate in the system. In the case of scale-free
networks, on the other hand, this threshold becomes vanishingly small in the
limit of infinite system size. We find that the initial rate at which a rumour
spreads is much higher in scale-free networks than in random graphs, and that
the rate at which the spreading proceeds on scale-free networks is further
increased when assortative degree correlations are introduced. The impact of
degree correlations on the final fraction of nodes that ever hears a rumour,
however, depends on the interplay between network topology and the rumour
spreading rate. Our results show that scale-free social networks are prone to
the spreading of rumours...