Sharif Digital Repository

Vaccination is one of the ways of disease control and prevention, which not only protect individuals against the disease, but also reduce the disease spread rate. Mass vaccination of individuals is not always possible due to the high cost and limitation of immunization resources. Therefore, researchers are always seeking solutions to find the persons that their immunization may have a greater impact in reduction of disease spread rate. The advent of network epidemic models and the possibility of removal the secured nodes in those models, showed that this problem is equivalent to finding a limited set of individuals that their removal will eliminate or minimize the number of people at risk of... 

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,... 

Nowadays Systems in different fields of research like computer science, biology, social networks, information networks, and economics are modeled as graphs. The graphs which model real world systems have very different topological characteristics than those of classic networks. One of the prominent characteristics of these networks, is that its not practical to describe a general model for their structure and behavior. As a consequence of this complexity in modeling and structure, these networks are called complex networks. One of the most important observations in complex networks is the presence of communities, it means that in such networks one can separate vertices in disjoint sets, such... 

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... 

In this thesis, first we will have a thorough review on problems and models presented in the field of contagion in networks (spread of diseases, spread of computer viruses,etc.). Then we will investigate the basic model of virus inoculation game with purely selfish players and the modified version of it which takes into account a factor of friendship. We will discuss the results of these models including computing and comparing Nash Equilibria  

Online social networks have become very popular in recent years. Most people usually get involved in multiple social networks to enjoy new contents and different social interactions. Many new social networks try to attract users of other existing networks to increase the number of their users. Once a user (called source user) of a social network (called source network) joins a new social network (called target network), a new internetwork link, known as anchor link, is formed between the source and target networks. In this thesis, we concentrate on predicting the formation of such anchor links between heterogeneous social networks. Unlike conventional link prediction problems in which the... 

In inefficient stock markets, fast and complete access to the public information about stocks and using this information for trades can make the investment more profitable. This research gathered the Iranian telegram channel's data with stock and investment subjects, trading volume, and stock returns. We suggested a trading strategy for beating the market by processing these data. We have also investigated the transaction costs in this research.
 

Stock market prediction has always been a challenging task. Due to its stochastic nature, naive models cannot help solve the problem. In the past, Statistical models were used, however nowa- days with the rise of deep learning and more complex models, aggregating data, in order to pre- dict the stock price, has become feasible. Moreover, the emergence of social networks enables researchers to design models for stock prediction.Researchers used recurrent networks and word vector representations to solve this problem. However, recently newer models such as generative models based on VAEs and attention have gained interest. Newer models also don’t rely on a single data source and use multiple... 

Health influencers leveraged social networks to connect with people and society during the Covid-19 crisis. Platforms like Twitter served as suitable channels for disseminating published messages through word-of-mouth communication. In times of crises like Covid-19, individuals and organizations involved in managing the situation harnessed this capability, contingent upon the quantity and quality of word-of-mouth exchanges. During public crises, public polarity and sentiment toward the issue and the maintenance of public morale hold paramount significance. Consequently, crafting messages that garner positive word-of-mouth communication became a focal point for health influencers. In this... 

Interactions in social networks consist of positive relations, such as friendship, trust, like, and negative relations, such as antagonism, distrust, dislike. “Signed networks” are utilized to model these networks. These networks are presented by “signed graphs” in which nodes are the people and relations are modeled by sign of edges. One of the challenging problem in signed networks is link sign prediction, i.e., specifying unknown edge sign along with evolution of the network given sign of some edges and further information about remainder of network. Two approaches are used to answer this problem. The first approach is proposing computing models for sign prediction. In this assertion we... 

In this thesis, we attempt to construct a model that can predict whether someone will retweet a tweet. For this purpose, we construct a machine learning model and we use Twitter’s network features as our model’s input. We collect about 1300 random tweets and their retweets to make retweet cascades. By collecting or calculating users’ features in each retweet cascade, we construct our desired input data for our model. We test both random forest and neural networks as our machine learning section of the model. Random forest is the most accurate of the two models, predicting retweet actions with an accuracy of 0.89. Additionally, we find out that two features of the network have the greatest... 

One of the influential factors affecting the future price trends of a stock is the public sentiment surrounding that particular stock. In recent years, researchers have employed Natural Language Processing (NLP) techniques to analyze textual data present on social networks, aiming to investigate public opinions. However, there has been limited attention given to validating the users expressing opinions concerning the stock market. Much of the opinions shared on social networks lack a thorough examination and analysis of the market, often being solely based on the author's sentiments. This research endeavors to validate active users on the social network 'X' (Twitter) by developing a... 

Given a snapshot of a network, link preditction methods try to infer future intractions be-tween its nodes. These methods may be used in either analyzing current state of the network or predicting future links of it. Link prediction techniques have many applications among which we can mention recommendation systems. These systems are implemented for com-mercial reasons or preventing user confusion in huge amount of information available.A new perspective toward link prediction is based on supervised random walk. In such methods, a random walker starts from a node in the network and randomly traverses to one of the current node’s neighbours with a probability proportional to the chosen link’s... 

The topic of influencing and regulating the behavior of communities is one which has always gathered attention by various governments, civic institutions, organizations and individuals. Research in this topic has recently been accelerated with the expansion of large scale online social networks. The massive moment of user data which exists in such settings has led to various researchers investigating methods to create new social behaviors such as habits, values and norms, with the core of these methods being the flow of ideas between social actors in order to create such social habits and behaviors.In this context, social norms are a core concept in social sciences and play a critical role... 

Nowadays, in our contemporary societies the social networks and online communities have carved for themselves a crucial niche and unique status. Maintaining and enhancing a core relation between their communities, thus have proven to be a worthy challenge to IT professionals. We have proposed a model for developing and maintaining a cohesive relation between members in social networks and improved their interaction and cooperation via collaboration of different social networks .We focus on the definition and properties of transitivity and semantic attributes ,which explains the relationship between members’ attributes and their membership level in social networks and leading us to provide... 

Many real-world communication systems such as Internet, online social networks, and brain networks can be modeled as a complex network of interacting dynamical nodes. These networks have non-trivial topological features, i.e., features that do not occur in simple networks such as lattices or random networks. The tremendous growth of Internet and its applications in recent years has resulted in creation of large-scale complex networks involving tens or hundreds of millions of nodes and links. Thus, it may be impossible or costly to obtain a complete picture of these large networks, and sampling methods are essential for practical estimation of network properties. Therefore, in this thesis, we... 

Many studies has been focused on extracting structural and behavioral properties of complex networks in recent decade. Online Social Networks (OSNs) are one example of complex networks. Nowadays with rapid growth of OSNs such as Facebook and Twitter, the study of OSNs has become an interesting research area. Many of recent OSN studies studied friendship networks. Friendship network is a binary unweighted network, and all of its links have the same importance. But, in reality not only all friendship links are not representative of social interactions, but also the social links have a variety of intimacy, intensity, and etc. So, all links should not be considered equal. Recently researchers... 

Social networks play an important role in people’s lives and have substantial economic outcomes. The role of referrals in labor market, mutual funds in developing countries, the spread of diseases and information, advertisements of goods and services, and political campaigns are just a few examples. Here we propose a strategic network formation model and calibrate and test it with Facebook data. The main idea in this model is that people don’t decide on creating links with others based on individual-link cost-benefit analysis, rather they participate in different social groups and creating links with others are a byproduct of this group participation. Our model does well with regard to... 

Traditional security approaches prevented participants of an environment from malicious behavior by closely monitoring every transaction of the network. Such approaches are very costly in modern autonomous systems, besides, they are also impossible to apply in many cases. Trust management mechanisms are developed in order to ensure safe interactions with unknown parties in such open environments. Most trust management mechanisms rely on testimonies of interaction participants as the source of information to estimate a peer’s reputation. The first challenge that arises here is the lack of incentives for providing such information. Even if interaction parties are encouraged to report the... 

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