3,965 research outputs found

    Epidemic processes in complex networks

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    In recent years the research community has accumulated overwhelming evidence for the emergence of complex and heterogeneous connectivity patterns in a wide range of biological and sociotechnical systems. The complex properties of real-world networks have a profound impact on the behavior of equilibrium and nonequilibrium phenomena occurring in various systems, and the study of epidemic spreading is central to our understanding of the unfolding of dynamical processes in complex networks. The theoretical analysis of epidemic spreading in heterogeneous networks requires the development of novel analytical frameworks, and it has produced results of conceptual and practical relevance. A coherent and comprehensive review of the vast research activity concerning epidemic processes is presented, detailing the successful theoretical approaches as well as making their limits and assumptions clear. Physicists, mathematicians, epidemiologists, computer, and social scientists share a common interest in studying epidemic spreading and rely on similar models for the description of the diffusion of pathogens, knowledge, and innovation. For this reason, while focusing on the main results and the paradigmatic models in infectious disease modeling, the major results concerning generalized social contagion processes are also presented. Finally, the research activity at the forefront in the study of epidemic spreading in coevolving, coupled, and time-varying networks is reported.Comment: 62 pages, 15 figures, final versio

    Quantifying Information Overload in Social Media and its Impact on Social Contagions

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    Information overload has become an ubiquitous problem in modern society. Social media users and microbloggers receive an endless flow of information, often at a rate far higher than their cognitive abilities to process the information. In this paper, we conduct a large scale quantitative study of information overload and evaluate its impact on information dissemination in the Twitter social media site. We model social media users as information processing systems that queue incoming information according to some policies, process information from the queue at some unknown rates and decide to forward some of the incoming information to other users. We show how timestamped data about tweets received and forwarded by users can be used to uncover key properties of their queueing policies and estimate their information processing rates and limits. Such an understanding of users' information processing behaviors allows us to infer whether and to what extent users suffer from information overload. Our analysis provides empirical evidence of information processing limits for social media users and the prevalence of information overloading. The most active and popular social media users are often the ones that are overloaded. Moreover, we find that the rate at which users receive information impacts their processing behavior, including how they prioritize information from different sources, how much information they process, and how quickly they process information. Finally, the susceptibility of a social media user to social contagions depends crucially on the rate at which she receives information. An exposure to a piece of information, be it an idea, a convention or a product, is much less effective for users that receive information at higher rates, meaning they need more exposures to adopt a particular contagion.Comment: To appear at ICSWM '1

    Global attractors and extinction dynamics of cyclically competing species

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    Transitions to absorbing states are of fundamental importance in nonequilibrium physics as well as ecology. In ecology, absorbing states correspond to the extinction of species. We here study the spatial population dynamics of three cyclically interacting species. The interaction scheme comprises both direct competition between species as in the cyclic Lotka-Volterra model, and separated selection and reproduction processes as in the May-Leonard model. We show that the dynamic processes leading to the transient maintenance of biodiversity are closely linked to attractors of the nonlinear dynamics for the overall species' concentrations. The characteristics of these global attractors change qualitatively at certain threshold values of the mobility and depend on the relative strength of the different types of competition between species. They give information about the scaling of extinction times with the system size and thereby the stability of biodiversity. We define an effective free energy as the negative logarithm of the probability to find the system in a specific global state before reaching one of the absorbing states. The global attractors then correspond to minima of this effective energy landscape and determine the most probable values for the species' global concentrations. As in equilibrium thermodynamics, qualitative changes in the effective free energy landscape indicate and characterize the underlying nonequilibrium phase transitions. We provide the complete phase diagrams for the population dynamics and give a comprehensive analysis of the spatio-temporal dynamics and routes to extinction in the respective phases

    Topological data analysis of contagion maps for examining spreading processes on networks

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    Social and biological contagions are influenced by the spatial embeddedness of networks. Historically, many epidemics spread as a wave across part of the Earth's surface; however, in modern contagions long-range edges -- for example, due to airline transportation or communication media -- allow clusters of a contagion to appear in distant locations. Here we study the spread of contagions on networks through a methodology grounded in topological data analysis and nonlinear dimension reduction. We construct "contagion maps" that use multiple contagions on a network to map the nodes as a point cloud. By analyzing the topology, geometry, and dimensionality of manifold structure in such point clouds, we reveal insights to aid in the modeling, forecast, and control of spreading processes. Our approach highlights contagion maps also as a viable tool for inferring low-dimensional structure in networks.Comment: Main Text and Supplementary Informatio

    Data Dissemination And Information Diffusion In Social Networks

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    Data dissemination problem is a challenging issue in social networks, especially in mobile social networks, which grows rapidly in recent years worldwide with a significant increasing number of hand-on mobile devices such as smart phones and pads. Short-range radio communications equipped in mobile devices enable mobile users to access their interested contents not only from access points of Internet but also from other mobile users. Through proper data dissemination among mobile users, the bandwidth of the short-range communications can be better utilized and alleviate the stress on the bandwidth of the cellular networks. In this dissertation proposal, data dissemination problem in mobile social networks is studied. Before data dissemination emerges in the research of mobile social networks, routing protocol of finding efficient routing path in mobile social networks was the focus, which later became the pavement for the study of the efficient data dissemination. Data dissemination priorities on packet dissemination from multiple sources to multiple destinations while routing protocol simply focus on finding routing path between two ends in the networks. The first works in the literature of data dissemination problem were based on the modification and improvement of routing protocols in mobile social networks. Therefore, we first studied and proposed a prediction-based routing protocol in delay tolerant networks. Delay tolerant network appears earlier than mobile social networks. With respect to delay tolerant networks, mobile social networks also consider social patterns as well as mobility patterns. In our work, we simply come up with the prediction-based routing protocol through analysis of user mobility patterns. We can also apply our proposed protocol in mobile social networks. Secondly, in literature, efficient data dissemination schemes are proposed to improve the data dissemination ratio and with reasonable overhead in the networks. However, the overhead may be not well controlled in the existing works. A social-aware data dissemination scheme is proposed in this dissertation proposal to study efficient data dissemination problem with controlled overhead in mobile social networks. The data dissemination scheme is based on the study on both mobility patterns and social patterns of mobile social networks. Thirdly, in real world cases, an efficient data dissemination in mobile social networks can never be realized if mobile users are selfish, which is true unfortunately in fact. Therefore, how to strengthen nodal cooperation for data dissemination is studied and a credit-based incentive data dissemination protocol is also proposed in this dissertation. Data dissemination problem was primarily researched on mobile social networks. When consider large social networks like online social networks, another similar problem was researched, namely, information diffusion problem. One specific problem is influence maximization problem in online social networks, which maximize the result of information diffusion process. In this dissertation proposal, we proposed a new information diffusion model, namely, sustaining cascading (SC) model to study the influence maximization problem and based on the SC model, we further plan our research work on the information diffusion problem aiming at minimizing the influence diffusion time with subject to an estimated influence coverage

    Calling for Change? Innovation, diffusion, and the energy impacts of global mobile telephony

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    Few technologies in history diffused as intensively and fast as mobile phones, to the point where they have become the most democratic technology. The article analyzes historical patterns of mobile phone growth and their effects in energy needs. Through an empirical analysis employing diffusion models on data for 227 countries between 1980 and 2010, it is concluded that global demand may saturate at around one subscription per person and the diffusion of mobile-broadband connection has contributed to sustain growth. Demand has already showed signs of saturation in developed countries, while there is still potential for growth in developing countries. Impacts on energy consumption are assessed with the help of a field trial. Even though the energy consumed in phone charging was not very significant (6-8TWh) in 2010, it becomes substantially higher when infrastructural needs are included (93TWh). The actual trends suggest that mobile communication might have a sizeable direct effect on energy consumption—although the net impact on energy demand is more difficult to estimate. This can become an issue in developing countries, where the adoption of mobile phones is catching-up rapidly with the world average, in a context of generalized increasing electricity demand
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