Social networks collected by historians or sociologists typically have a large number of actors and edge attributes. Applying social network analysis (SNA) algorithms to these networks produces additional attributes such as degree, centrality, and clustering coefficients. Understanding the effects of this plethora of attributes is one of the main challenges of multivariate SNA. We present the d...

Social networks collected by historians or sociologists typically have a large number of actors and edge attributes. Applying social network analysis (SNA) algorithms to these networks produces additional attributes such as degree, centrality, and clustering coefficients. Understanding the effects of this plethora of attributes is one of the main challenges of multivariate SNA. We present the d...

the aim of this paper is to determine if the centrality degree and density of latin-american and caribbean countries (la-c) predicts their citation based performance in academic research in the management discipline. for our analysis, we use publication data of the social science citation index in the field of ‘‘management’’ between 1988 and 2013, extracted from isi web of science. the resultin...

Social network analysis has attracted intensive interests by researchers from multiple disciplines. However most of the existing work is descriptive nature, and statistical network analysis remains an active area of research. In this paper, we model and study two facets of the social networks in short message services (SMS). One is the structure of the contact networks of mobile users, the othe...

Whereas the use of Enterprise Social Networks (ESN) is a pervasive topic in research and practice, both parties are still struggling to come to a better understanding of the role and impact of ESN in and on knowledge-intensive corporate work. As a part of this phenomenon, employees who communicate their knowledge in ESN helping other users to do their daily work play a decisive role. We need to...

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...

Social networks have known an important development since the appearance of web 2.0 platforms. This leads to a growing need for social network mining and social network analysis (SNA) methods and tools in order to provide deeper analysis of the network but also to detect communities in view of various applications. For this reason, a lot of works have focused on graph characterization or cluste...

Social networks existing among employees, customers or other types of users of various IT systems have become one of the research areas of growing importance. Data about people and their interactions that exist in social media, provides information about many different types of relationships within one network. Analysing this data one can obtain knowledge not only about the structure and charac...

Network science has released its talents in social network analysis based on the information of static topologies. In reality social contacts are dynamic and evolve concurrently in time. Nowadays they can be recorded by ubiquitous information technologies, and generated into temporal social networks to provide new sights in social reality mining. Here, we define circle link to measure contextua...