Revisiting Node Centrality of Social Network Analysis
Unfortunately, this opportunity is currently unavailable. Please check back at a later date.
After revisiting all present node centrality measures of social network analysis, this research aims to develop new algorithm for quantifying three common measures of node centrality (i.e., degree, closeness, and betweenness) for any weighted goal-oriented social networks.
This project aims to develop new algorithm and method for quantifying three common measures of node centrality (i.e., degree, closeness, and betweenness) for any weighted goal-oriented social networks. There has been substantial amount of research for developing new approach and method to measure different social network centrality measures. Some of those approaches are more appropriate for static network (e.g., Freeman’s approach) while some others are developed for dynamic weighted networks (e.g., Newman’s approach). However, none of these approaches consider the constraint (or, goal or target) of the network under consideration in measuring these centrality measures. How does anyone compare the network position of a physician in a physician collaboration network (which has in total hundred physicians and provides services of fifty patients) with the network position of other physician who is part of another physician collaboration network (which has in total hundred physicians and provides services to hundred patients)? These two networks have different level of target/goal - the first network provides services to fifty patients while the second network provides services to hundred patients. The existing network measures, from both static and dynamic network perspective, cannot provide a valid comparison for this scenario. This project therefore intends to develop new algorithm for measuring different node centrality measures, which will eventually open new rooms: (i) for analyzing the dynamics of complex networks more accurately; (ii) for developing efficient approaches to compare different networks and the associate level of their actors’ network involvement; and (iii) will overcome the drawbacks of existing node centrality measures.
Want to find out more?
The opportunity ID for this research opportunity is: 1565
Other opportunities with Dr Shahadat Uddin
- Complex Coordination Dynamics in Disaster Response
- Big data analytics: The case of longitudinal (and computerised) health insurance claims datasets
- Structural dynamics and their impact on network robustness for longitudinal networks
- Dynamics of Peer Counselling, Mothers and Family Social Networks for infant and young child feeding