Capturing actor-level dynamics of longitudinal networks

Study of the dynamics of longitudinal networks has already attracted enormous research interest. Although dynamics of networks can be captured both at network-level and node / actor-level, the latter has gained less attention in current literature. By following a topological approach (i.e., static topology and dynamic topology) to analyze networks, this paper first proposes a research framework to capture actor-level dynamics for longitudinal networks. In static topology, Social Network Analysis (SNA) methods are applied on the aggregated network of entire data collection period. A smaller segment of network data that are accumulated in less time compared to the entire data collection period are used in dynamic typology for analysis purpose. This study further successfully compiles and applies this framework to the context of organizational crisis and project dynamics with the purpose to explore different level of actor-level dynamics at the different operational environment of these contexts over time. It is noticed that different level of actor-level dynamics are observed in the communication and collaboration network during the different facets of the organizations. In the context of organizational crisis, it is evident that during the 'crisis' period of operational running of organization, actors in the organizational email communication networks show higher level of actor-level dynamics compared to the 'normal' period. Less actor-level dynamics are observed during the 'final' phase of project life cycle, as found from the second context.