PhD student in Information Systems and Innovation
Research Interests
Thesis: 'Social networks as a phenomenon and a field of study: the practical, methodological and theoretical implications of emerging ICTs'
The study of social networks spells out the mutual influence between the actions of actors and the structure of social inter-connections in which they are embedded. But the patterns of social interaction are changing thanks to the growing use of technological innovations, such as electronic mail, wikis, peer-to-peer communication, online social networks and micro-blogging. Each platform presents its unique set of norms and a range of idiosyncratic practices of interaction and collaboration. What are the implications of these trends for the study of social networks? This research demonstrates how new modes of communication and collaboration cultivate new types of social phenomena. It exposes researchers to datasets with unique properties, ultimately challenging traditional methods of measuring and modelling social action.
To achieve this aim, this study compares ‘traditional’ network datasets with the data yielded from electronically-mediated interactions, also known as ‘action datasets’. The main differences are found to be the process of data collection, the data’s scope and scale and, above all, the nature of the phenomena it represents. I further identify and discuss the implications of these differences on research practices, specifically on the methods of data modelling and analysis but also on the type of theoretical questions which the data can address Finally, I demonstrate how this analysis motivates the use of network models with two or more modes (that is, the type of entities represented in the network) to capture more of the richness of the original datasets. This new method adds to the network's potential to explain social phenomena.
Supervisor