Protecting the identities of the actors along with their sensitive information has become a matter of concern for the organizations which are publishing huge amounts of data every day for the purpose of research. Recent studies have shown that simply removing the sensitive labels associated with the actors do not guarantee their privacy protection. The structural property of the graph associate...

To date publish of a giant social network jointly from different parties is an easier collaborative approach. Agencies and researchers who collect such social network data often have a compelling interest in allowing others to analyze the data. In many cases the data describes relationships that are private and sharing the data in full can result in unacceptable disclosures. Thus, preserving pr...

Social commerce is the latest development in e-commerce to combine the power of online social networking with shopping. While the adoption of information technology is well studied, new theoretical development is needed to account for the specific characteristics of social commerce applications and their interactions with the user. This study examines factors that are associated with user accep...

With the recent surge of social networks such as Facebook, new forms of recommendations have become possible – recommendations that rely on one’s social connections in order to make personalized recommendations of ads, content, products, and people. Since recommendations may use sensitive information, it is speculated that these recommendations are associated with privacy risks. The main contri...

Depression is one of the most common mental health problems among young adults, which is often associated with many other negative health and social problems. Despite numerous studies about depression and its transmission in the offline environment, there are few studies investigating how depression is transmitted on Social Network Sites (SNS). In this study, we build a new theory about depress...

A growing body of research leverages social network based trust relationships to improve the functionality of the system. However, these systems expose users’ trust relationships, which is considered sensitive information in today’s society, to an adversary. In this work, we make the following contributions. First, we propose an algorithm that perturbs the structure of a social graph in order t...

This synthesis lecture provides a survey of work on privacy in online social networks (OSNs). This work encompasses concerns of users as well as service providers and third parties. Our goal is to approach such concerns from a computer-science perspective, and building upon existing work on privacy, security, statistical modeling and databases to provide an overview of the technical and algorit...

Online Social Networks (OSNs) offer access control mechanisms to protect users’ sensitive information from undesired accesses. Yet, their information is still vulnerable to disclosure when their friends assign conflicting privacy policies: a user prohibits everyone from accessing his own content or profile but his friends allow others to see it. OSNs tend to select Permit-Take-Precedence when r...

Social networks, patient networks, and email networks are all examples of graphs that can be studied to learn about information diffusion, community structure and different system processes; however, they are also all examples of graphs containing potentially sensitive information. While several anonymization techniques have been proposed for social network data publishing, they all apply the a...

Social workers have the task of addressing issues that are unique to ethnic minority youth in clinical practice; however, they may be ill equipped to begin practice with these youth due to a lack of specificity within generalist curricula. Using African-American youth as an example, the paper provides evidence that there are critical areas of development and functioning that diverge from the ge...