5 research outputs found

    Competitive Dynamics between Physical and Virtual Markets in Multiplex Networks

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    Despite having interesting results of analyzing the adoption of e-commerce using social networks, diffusion does not occur in a single-layered network. There is sufficient evidence that game theory, complex networks and Theory of Planned Behavior are suitable frameworks to represent some part of the dynamics of innovation diffusion. However, it is necessary to integrate this methodological triplet to accept that an emergent behavior is generated by more real causes. We analyzed the effect of the multiplex topology when people decide to make transactions through virtual or physical channels, and found that connectivity is a key issue when managing the agent’s behavior. This also translates into greater coordination in the agents' decisions. When a multiplex is formed by at least one network with very efficient information flow, this network will govern the dynamics affecting channel selection and will also reduce transaction uncertainty. In addition, we found that investing in connectivity is worthwhile when trust is low in at least one channel; otherwise, it does not have enough impact to increase current transactions. This article makes a significant methodological contribution by showing a new way to analyze the impact of multiplex social networks, as well as a practical contribution by evidencing the effects of the structures on both intentions and actions

    A Novel Location Free Link Prediction in Multiplex Social Networks

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    In recent decades, the emergence of social networks has enabled internet service providers (e.g., Facebook, Twitter and Uber) to achieve great commercial success. Link prediction is recognized as a common practice to build the topology of social networks and keep them evolving. Conventionally, link prediction methods are dependent of location information of users, which suffers from information leakage from time to time. To deal with this problem, companies of smart devices (e.g., Apple Inc.) keeps tightening their privacy policy, impeding internet service providers from acquiring location information. Therefore, it is of great importance to design location free link prediction methods, while the accuracy still preserves. In this study, a novel location free link prediction method is proposed for complex social networks. Experiments on real datasets show that the precision of our location free link prediction method increases by 10 percent

    Spreading processes in Multilayer Networks

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    Several systems can be modeled as sets of interconnected networks or networks with multiple types of connections, here generally called multilayer networks. Spreading processes such as information propagation among users of an online social networks, or the diffusion of pathogens among individuals through their contact network, are fundamental phenomena occurring in these networks. However, while information diffusion in single networks has received considerable attention from various disciplines for over a decade, spreading processes in multilayer networks is still a young research area presenting many challenging research issues. In this paper we review the main models, results and applications of multilayer spreading processes and discuss some promising research directions.Comment: 21 pages, 3 figures, 4 table
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