This is an event in the CSIRO IR & Friends series.
Large majority of statistical analyses of both offline and online social networks based their studies on methods for static networks, even though most ofsocial networks are dynamic. Online social networks provide us frequently with aunique opportunity to be able to access exact data of human online (inter)actions, including the precise times of those actions. As opposed to using modelling approaches for static or panel network data, oftenbetter ways of studying what happened in online social networks is to analyse the exact behaviour of users and the network growth as it happened, by using dynamic/longitudinal methods. This presentation gives a short introduction to some of the possibilities of dynamic network analysis. A very basic introductionto tnet R framework will be provided. Dynamic network modeling will be illustrated on a Twitter Advocacy network, and results of the models will be discussed.