background global health partnerships have grown rapidly in number and scope, yet there has been less emphasis on their evaluation. gavi, the vaccine alliance, is one such public-private partnership; in gavi-eligible countries partnerships are dynamic networks of immunization actors who work together to support all stages and aspects of gavi support. this paper describes a conceptual framework ...

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 analysis (SNA) is not a formal theory in sociology but rather a strategy for investigating social structures. As it is an idea that can be applied in many fields, we study, in particular, its influence in the information sciences. Information scientists study publication, citation and cocitation networks, collaboration structures and other forms of social interaction networks. Mo...

To better address questions concerning animal sociality, animal behaviorists and behavioral ecologists are increasingly turning to the suite of analytical techniques known as social network analysis (SNA). SNA allows for the quantifi cation of multi-actor interactions, thereby providing a more realistic representation of social patterns and relationships. Here, we provide a brief introduction t...

Terrorist Activities worldwide has approached the evolution of various high-ended methodologies for analyzing terrorist groups and networks. Existing research found that Social Network Analysis (SNA) is one of the most effective and predictive method for countering terrorism in social networks. The study reviewed various SNA measures for predicting the key players/ main actors of terrorist netw...

In this paper, we discuss the use of Bayesian belief networks as a tool for enhancing social network analysis. Traditional social network analysis (SNA) primarily uses graph-theoretic algorithms to compute properties of nodes in a network. However, these algorithms assume a degree of completeness and reliability of the social network data, which cannot always be assured. Applying Bayesian belie...

Social Network Analysis (SNA) tries to understand and exploit the key features of social networks in order to manage their life cycle and predict their evolution. Increasingly popular web 2.0 sites are forming huge social network. Classical methods from social network analysis (SNA) have been applied to such online networks. In this paper, we propose leveraging semantic web technologies to merg...

Social networks are flourishing because of fast growing Internet and the World Wide Web, and more research efforts have been put on Social Network Analysis (SNA). A social network can be modeled like a graph, where the nodes represent persons, and an edge between them represent direct relationship between the persons. One of the issues in SNA is to identifying criminals from groups of individua...