Modern social network analysis—the analysis of relational data arising from social systems—is a computationally intensive area of research. Here, we provide an overview of a software package which provides support for a range of network analytic functionality within the R statistical computing environment. General categories of currently supported functionality are described, and brief examples...

Social network research relies on a variety of data sources, depending on the problem scenario and the questions, which the research is trying to answer or inform. Social networks are very popular nowadays and the understanding of their inner structure seems to be promising area. Cluster analysis has also been an increasingly interesting topic in the area of computational intelligence and found...

This chapter examines the area of social computing and its implications for electronic government (e -government). Social computing is a broad term that refers to different products and services that supports human interaction in a computer mediated environment. Terms such as online communities, peer networking, and social software have overlapping meanings with social computing (Parameswaran a...

one of the most important issues related to knowledge discovery is the field of comment mining. opinion mining is a tool through which the opinions of people who comment about a specific issue can be evaluated in order to achieve some interesting results. this is a subset of data mining. opinion mining can be improved using the data mining algorithms. one of the important parts of opinion minin...

Social networks provide a rich source of graph drawing problems, because they appear in an incredibly wide variety of forms and contexts. After sketching the scope of social network analysis, we establish some general principles for social network visualization before finally reviewing applications of, and challenges for, graph drawing methods in this area. Other accounts more generally relatin...