Sharif Digital Repository

Communication among people over the emerging networks has been the focus of attention in different branches of science during last decades. Online Social Networks (OSNs), with more than hundreds of millions of users are powerful means for directing information within and across societies. Thus, studying various aspects of OSNs is an important issue for researchers. Due to large number of users and friendship relationships among them, gathering complete information from an OSN is not feasible. On the other hand, hiding users information and crawlers limitations are challenges for gathering complete data. A Common solution for this problem is Sampling from OSNs. Sampling from OSNs (and... 

The dynamic behavior of networks largely depends on their structural properties. The information or failures can spread through the links of complex networks constructed by people or agents, and their physical and informational contacts. In this research, the process of network diffusion was investigated in different model and real networks. In particular, we focused on ”cascaded failure” and ”viral marketing” which are among the major topics that have attracted much attention in this context. Firstly, we investigated the robustness of modular complex networks against random and systematic component failures. Many real-world networks have modular structure and they may undergo random errors... 

Nowadays trust has become one of the main challenges of every online social network. The open and decentralized nature of Peer-to-Peer network makes it vulnerable to be exploited by malicious users to distribute tampered and harmful contents. We propose a dynamic computational trust model based on a neuro-fuzzy approach and implemented it on Gnutella network. The model is a novel application of control systems approach for evaluating trust and reputation in P2P networks. We utilize Local Linear Model Tree (LOLIMOT) to perform a nonlinear dynamic system identiffcation and thus to approximate trust. The performance of our reputation-based trust model is evaluated by simulation. We create a... 

The diffusion process propagates information, viruses, ideas, innovations and new be-haviours over social networks. Adopting a new behaviour, which is mentioned as an in-fection, starts from a little group of people. Spreading it over more neighbors and friendscan result in an epidemic phenomenon over the network. As this infection propagates, aninformation cascade will be generated. The spread of information cascades over social net-works forms the diffusion networks. Although observing the infection time of a person ispossible, determining the source of infection is usually a difficult problem. Additionally, inmany applications we can not observe the underlying network which diffusion... 

The control and management of social networks’ potentials has been an important research subject for many organizations and researchers in recent years. Social network of an organization includes all the people that at least once have established a social relationship with the organization directly or indirectly. This relationship can be formal or informal, spontaneous or controlled, and deep or shallow. But in any case, the stronger the communication between people’s social relationships (as members of that social network) become and the more increases in the number of members of that social network, the easier path to success the organization could achieve. Hence, the critical success... 

With the development of social network sites and wide use of Social Networks, information security and confidence of its components, became more and more important and turned into subject of many studies and researches. Relationship based on trust besides increasing productivity reduces risk of information transmission to non-related people. Although in the real world, semantic relations are the main basics for trust, but the existing methods of trusting in current sites have less attention to this point. To reduce such issues, firstly this research is going to use an added semantic understanding on top of the social networks structure. To do so, there is an inference engine in addition to a... 

Online Social Networks have become indispensable platforms to model social interactions and for the retrieval of knowledge based on economical, political, social and ... criteria. The importance of social networks for such uses stems from the vast amount of social data that it gathers for use by researchers. Aside from it’s impact on the field of social network analysis, the ever-growing use of social media by users has added even more importance to social network data as it contains a history of the users virtual life. Unfortunately research on proposals to support the management of this vast amount of data, whether for the conceptual modeling of social data or to provide a uniform modeling... 

In this thesis, we study the treewidth of social networks. The importance of studding treewidth is for two reasons. The first is that for the graph with bounded treewidth, many optimization problems that are NP-hard in general, can be solved in polynomial or even linear time. The second is that the high value of treewidth in a graph, reflects some high degree of connectivity and robustness, which is an essential factor in designing many networks. But the problem is that determining the value of treewidth in a graph is NP-complete so, computing the treewidth of real complex networks is not feasible. We first review the related works and mention the weakness of the past works, then introduce a... 

Networked business is a kind of businesses, relatively new and very complex, worthy of more analysis and study. From all types of networked businesses, “Platform based” ones are subject of this study. To solve “the problem of networked business”, in this study we try to develop a conceptual framework, using different disciplines especially:
- Business model studies
- Network science and social network studies
- Economic and strategic studies of platforms
Besides some new business concepts defined and theorized in this study, reader will find the conceptual architecture, applicable to the general of the business  

The fast growth of social networks and their wide range of applications have made the anal-ysis of them an interesting field of research. The growth of concern in modeling large social networksand investigation of their structural features leads studies towards community detec-tion in such networks. In recent years, a great amount of effort has been done for introducing community detection algorithms, many of which are based on optimization of a global cri-terion which needs network’s topology. However, because of big size of most of the social networks , accessing their global information tends to be impossible. Hence, local commu-nity detection algorithms have been introduced. In this... 

Networked computers are expanding more and more around the world, and digital social networks becoming of great importance for many people's work and leisure. Emails, Weblogs and Instant Messengers are popular instances of social networks. In this thesis, the main target is to have an advertisement according to user favorites and interests by mining his/her interactions in digital social networks. Briefly, in our method social network users are categorized based on the topics exchanges between them in the network, these topics discovered by mining of flowing data in that environment, considering that these topics shows the user willing, finally relevant advertisements will be represented to... 

Social networks play a fundamental role as a media for the spread of inuence among its members. How people like to adopt innovation from their friends is known as word-of-mouth eect and has a long history of study in social science and recently in computer science and mathematics. In this context, The Inuence Maximization Problem is about nding initial active set of specic size in order to maximize the nal adoptions in the network through diusion of inuence. The optimization problem of the most inuential nodes selection is NPhard. As a result, some heuristic algorithms are needed to approximate the nal result. In this thesis some new heuristic algorithms were proposed with respect to... 

Increasing in social communication via electronic ways has been made social network analysis of these communications more important each day. One of the most important aspects in social network analysis is community detection in such networks. There are many different ways to extract communities from social graph structure which in some of them the content of communication between actors has been noticed in community extraction algorithm. In this thesis after a short survey over advantages and disadvantages of existing methods for community detection, a new method for extracting communities from social networks has been suggested which in addition to streaming property of data it spot the... 

Social network is a map of relationships among individuals or organizations. With the development of social network sites (SNS), security protection of private information online has been a serious and important research topic. Information in social networks is online all the time and available to a large number of visitors. The main problem in current SNSs is that, people are not able to define different categories for their relations and then they cannot have good self-defined privacy policies. Also default policies cannot satisfy different environments and cultures and will serve information to strangers. After that different social networks with different interfaces are not... 

Growth of tools that ease sharing information and resources in social networks can cause privacy issues for the users. Protecting user’s personal information against unauthorized access is a crucial task, and it is considered as a first step for preserving user’s privacy in such networks. Policies, access control rules, and the way rules are applied to online social networks are issues that are less investigated and most existing frameworks have used simple models. Growth of users joining social networks and significant volume of resources shared in these networks make such environments suitable for using semantic technology. Semantic technology is used for modeling various resources, users,... 

The auction models are one of the fundamental issues of economics. So far, the bidders were assumed independent of one another in auction models. In this thesis the bidders are considered as a social network. Bidding of an agent influences bidding behavior of other agents based on the network among them. Considering social network among the buyers, we study seller's optimal strategy  

Information cascade or affection in a broad social network is introduced as a dynamic epidemic phenomenon in the society. As people notify a new innovation, technology, or hobby, they try to share it with their friends, colleges or neighbors. Till now most of the cascade models are presented for unsigned network, in which all links have the same sign (such as friends and trusted networks). In these networks cascade is independent of the edge sign. But in reality signed networks are as common as simple networks. Thus, in this thesis, we study information cascade in networks with positive and negative edges. We link the cascade size to community structure of signed networks; communities are... 

Nowadays, Online Social Networks (OSNs) play an important role in the exchange of information among people. Some previous studies indicate that diffusion behavior and network structure are tightly related. Community structure is one of the most important features of OSNs. Access to the whole network topology is the necessary and prevalent requirement for most of community detection methods, so the limited access to full or partial topology can decrease their accuracy. Using traceable information over diffusion network is a solution to surmount this difficulty. In this work, we are concerned with the community detection by only using the diffusion information, while unlike the previous... 

Trust prediction, the ability to identify how much to trust to allocate an unknown user, is an important prerequisite toward the development of scalable on-line e-commerce communities. We are more likely to purchase an item from a seller on an e-commerce websites such as eBay or Amazon, if our trusted acquaintances have reported positive experiences with that seller in the past. Reviews from trusted users will carry more weight towards the purchasing decision than reviews from anonymous or unknown customers. Thus, these platforms must support computational mechanisms for propagating trust between users. One of the significant challenges in the trust prediction problem is the unprecedented... 

Different models describing the procedure of epidemics are complicated and involving numerous factors. Some of these models that used a stochastic network for modelling epidemics had been successful in statistical prediction of spreading epidemics. However, in many cases there is no direct way to determine parameters of these models. In this thesis it has been desired to estimate those parameters based on historical data of epidemics To estimate structural parameters, concerning epidemic network, two independent inference have been studied. In the first inference, the probability of disease transmission from one person to another is estimated.
In the second, using Bayesian inference,...