Aboul Ella Hassanien (Abo)

Social Network Analysis (SNA) is becoming an important tool for investigators, but all the necessary information is often available in a distributed environment. Currently there is no information system that helps managers and team leaders to monitor the status of a social network. This chapter presents an overview of the basic concepts of social networks in data analysis including social networks analysis metrics and performances. Different problems in social networks are discussed such as uncertainty, missing data and finding the shortest path in social network. Community structure, detection and visualization in social network analysis is also discussed and reviewed. This chapter bridges the gap among the users by combining social network analysis methods and information visualization technology to help user visually identify the occurrence of a possible relationship amongst the members in a social network. In addition, briefly describing the different performance measures that have been encountered during any network analysis in order to understand the fundamental behind the comprehension. This chapter also, presents an online analysis tool called Forcoa.NET, which is built over the DBLP dataset of publications from the field of computer science, which is focused on the analysis and visualization of the co-authorship relationship based on the intensity and topic of joint publications. Challenges to be ad dressed and future directions of research are also presented and an extensive bibliography is included.order to understand the fundamental behind the comprehension. This chapter also, presents an online analysis tool called Forcoa.NET, which is built over the DBLP dataset of publications from the field of computer science, which is focused on the analysis and visualization of the co-authorship relationship based on the intensity and topic of joint publications. Challenges to be ad dressed and future directions of research are also presented and an extensive bibliography is included.

The continuous self-growing nature of social networks makes it hard to define a line of safety around these networks. Users in social networks are not interacting with the web only, but also with trusted groups that may contain enemies. There are different kinds of attacks on these networks including causing damage to the computer systems and steeling information about users. These attacks are not affecting individuals only, but also the organizations they are belonging to. Protection from these attacks should be performed by the users and security experts of the network. Advices should be provided to users of these social networks. Also security-experts should be sure that the contents transmitted through the network do not contain malicious or harmful data. This chapter shows the security risks and the tasks applied to minimize those risks. Explain the most famous ways that attackers and malicious use. Then show the security measures for each way. Also present a security guide and a social network security and privacy made in 2011, and finally a case study about the list of Foreign Terrorist Network dataset.

Computational social science is a new emerging field that has overlapping regions from Mathematics, Psychology, Computer Sciences, Sociology,and Management. Social computing is concerned with the intersection of social behavior and computational systems. It supports any sort of social behavior in or through computational systems. It is based on creating or recreating social conventions and social contexts through the use of software and technology. Thus, blogs, email, instant messaging, social network services, wikis, social bookmarking, and other instances of what is often called social software illustrate ideas from social computing. Social network analysis is the study of relationships among social entities. It is becoming an important tool for investigators. However all the necessary information is often distributed over a number of Web sites. Interest in this field is blossoming as traditional practitioners in the social and behavioral sciences are being joined by researchers from statistics, graph theory, machine learning and data mining. In this chapter, we illustrate the concept of social networks from a computational point of view, with a focus on practical services, tools, and applications and open avenues for further research. Challenges to be addressed and future directions of research are presented and an extensive bibliography is also included.

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