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 monitor the status of a social network. This chapter presents an overview of the basic concepts of social networks in data analysis including social network analysis metrics and performances. Different problems in social networks are discussed such as uncertainty, missing data and finding the shortest path in a social network. Community structure, detection and visualization in social network analysis is also illustrated. This chapter bridges the gap among the users by combining social network analysis methods and information visualization technology to help a user visually identify the occurrence of a possible relationship amongst the members in a social network. The chapter illustrates an online visualization method for a DBLP (Digital Bibliography Library Project) dataset of publications from the field of computer science, which is focused on the co-authorship relationship based on the intensity and topic of joint publications. Challenges to be addressed and future directions of research are presented and an extensive bibliography is also included.
CITATION STYLE
Ghali, N., Panda, M., Hassanien, A. E., Abraham, A., & Snasel, V. (2012). Social networks analysis: Tools, measures and visualization. In Computational Social Networks: Mining and Visualization (Vol. 9781447140542, pp. 3–23). Springer-Verlag London Ltd. https://doi.org/10.1007/978-1-4471-4054-2_1
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