Research that I am very interested in is based around social network analysis. We are looking at different aspects of these networks including level of degree for vertices as well as possible weighting methods we can employ to these vertices and the edges in the network to help find the most influential nodes in a network. We use datasets gathered from popular social networking sites. We have also been looking at Bottleneck identification and vertex clusterig techniques in these networks. The types of social networks we are most interested in are Facebook and Twitter connections.
The video displayed here shows users on Twitter who are talking about the London helicopter Crash on 16th Jan 2013. Where a user mentiones another an edge is formed between the two nodes. As time goes on if a user has not been mentioned in some time then they are removed from the network. This sort of timeseries visualisation shows how it is often the case that people who are local are the ones to report first and are then cited by the larger news organisations as time goes on.
A lot of our network analysis work has involved that of social media sites such as Facebook and Twitter. However, we have also had the opourtunity to look more towards other types of networks as well. In the summer of 2013 I was involved in a cross-disciplinary project with Institute of Integrative Biology that looked at co-expression of genes in cancer patients in an effort to attempt to slow down the progression of cancers. This was done through statistical analysis and construciton of biological gene co-expression networks where we could identify the most influential and active genes at different stages of the cancers. Once the genes have been located it is then possible to suppress thoes that become more active in the later stages of the cancer and stimulate thoes that are more active in the early stages.
I am also keenly interested in both transport networks and financial networks and what sort of applications our work can have in these areas.