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The modern science of networks has brought significant advances to our understanding of complex systems. One of the most relative features of graphs representing in real systems is community detection. The community detection can be considered as fairly independent compartments of a graph and a similar role play. It is an important problem in the analysis of computer networks, social networks, biological...
This paper proposes a public opinion propagation model on social networks based on SEIR. This model consider impacts of the node degree, social networks peculiar dissemination rules and users' habits, utilizes epidemiology and complex network theories, and establishes the dynamic evolution equations by building mathematical models of informed probability and disseminate probability. Simulation results...
We consider the problem of reaching consensus in a social network of agents described by the DeGroot model. We develop a measure for the efficiency with which consensus is reached, where the measure quantifies the transient behavior of public opinion around the consensus value. We then propose an optimization problem that maximizes consensus-reaching efficiency via the creation of new social links,...
While Collaborative Filtering (CF) recommender systems, which focus on previous indicate preferences, are known for their traditional problems such as cold-start, sparsity and modest accuracy, trust-based CF has been previously proposed to solve such issues by focusing on trust values among the users. Nonetheless, most existing approaches use trust as an independent factor from time, in this paper...
An Internet of Things (IoT) system connects a large amount of tags, sensors, and smart devices often with mobility to facilitate information sharing, enabling a variety of attractive applications. On the one hand, the service oriented architecture (SOA) can provide connectivity and interoperability among heterogeneous IoT devices in the physical network. On the other hand, IoT devices are virtually...
Recently the demand for using social networks to advertise has increased significantly, and viral marketing on social media has; therefore, become an effective approach when wishing to disseminate product advertisements, for it can help match customers to products more effectively than conventional marketing methods. This study measures the effectiveness of information dissemination within a dynamic...
A network model with both social and communication characteristics is considered. Different capacity regions are computed as a function of the social network size for each node. It has been shown that as the social connectivity among nodes improves, the likelihood of finding shorter path between source-destination pairs in the network increases which results in increase in the capacity compared to...
Location-based services have faced a development from being a hype to be used by a large user community at any place and time. However, only a few approaches exist, that take into account social interactions and learn from them in order to refine recommendations of points of interests accordingly. This paper analyzes the influence factors of mobile users for the choice of interests and derives an...
Thermodynamics, a concept thought of two centuries ago, refurbished and elaborated since, assimilated and transposed to distinctive disciplines stretching from neuroscience to economics but still lacks in-depth exploration of its impact on social networks. The aim is to model thermodynamic principles after social networks, to understand how different variables of the system such as entropy, temperature,...
Currently, social networks and social media have attracted increasing research interest. In this context, link prediction is one of the most important tasks since it can predict the existence or missing of a future relation between user members in a social network. In this paper, we describe experiments to analyze the viability of applying the within and inter cluster (WIC) measure for predicting...
The emergence of social computing enables users to intersect social behaviour with computing systems and to create social conventions as well as social contexts through the use of software and technology. Social networking sites have become popular to facilitate collaboration and knowledge sharing between users. A rich set of information is embedded in these social media data. In this paper, we propose...
Social collaboration scenarios, such as sharing resources between friends, are becoming increasingly prevalent in recent years. An example of this new paradigm is Social Cloud Computing, which aims at leveraging existing digital relationships within social networks for the exchange of resources among users and user communities. Due to their complexity, such platforms and systems have to be carefully...
Today, the churn phenomenon has been considered in many applications as an important outcome. Social networks can be considered as one of the most important applications with the mentioned outcome. Churn in social networks depends on the users' activity in a communication environment and appears if this activity is less than a required extent. Swarm Intelligence algorithms(SI), assumed to be the proper...
The current paper is an investigation towards understanding the navigational performance of humans on a network when the 'landmark' nodes are blocked. We observe that humans learn to cope up, despite the continued introduction of blockages in the network. The experiment proposed involves the task of navigating on a word network based on a puzzle called the word morph. We introduce blockages in the...
One of the issues to be resolved in social recommender systems is the identification of opinion leaders in a network. Finding effective people in societies has been a key question for many groups, e.g., marketers. The research undertaken in this paper focuses on finding important nodes in a network based on their behaviour as well as the structure of the network. This paper views the propagation of...
Modelling contagious diseases needs to incorporate in the models information about social networks through which the disease spreads out as well as data about demographic and genetic changes in the susceptible population, and also to include mechanistic knowledge about contacts between hosts and pathogens. We will introduce all these elements in two examples of contagious diseases, the obesity, a...
A number of recent studies on social networks are based on a characteristic which includes assortative mixing, high clustering, short average path lengths, broad degree distributions and the existence of community structure. Here, a model which satisfies all the above characteristics is developed. In addition, this model facilitates interaction between various communities. This model gives very high...
Real networks consisting of social contacts do not possess static connections. That is, social connections may be time dependent due to a variety of individual behavioral decisions based on current network connections. Examples of adaptive networks occur in epidemics, where information about infectious individuals may change the rewiring of healthy people, or in the recruitment of individuals to a...
A number of recent studies on social networks are based on characteristics which include assortative mixing, high clustering, short average path lengths, broad degree distributions and the existence of community structure. Here, a model which satisfies all the above characteristics is developed. In addition, this model facilitates interaction between different communities. This model gives very high...
We study a model of observational learning in social networks in the presence of uncertainty about agents' type distributions. Each individual receives a private noisy signal about a payoff-relevant state of the world, and can observe the actions of other agents who have made a decision before her. We assume that agents do not observe the signals and types of others in the society, and are also uncertain...
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