—This paper presents a novel methodology for social network discovery based on the sensitivity coefficients of importance metrics, namely the Markov centrality of a node, a metr...
With the development of emerging social networks, such as Facebook and MySpace, security and privacy threats arising from social network analysis bring a risk of disclosure of con...
—In this paper, we study the sensitivity of centrality metrics as a key metric of social networks to support visual reasoning. As centrality represents the prestige or importance...
Discovering communities from documents involved in social discourse is an important topic in social network analysis, enabling greater understanding of the relationships among act...
Ding Zhou, Isaac G. Councill, Hongyuan Zha, C. Lee...
—The hidden knowledge in social networks data can be regarded as an important resource for criminal investigations which can help finding the structure and organization of a crim...