Addressing structural and dynamic features of scientific social networks through the lens of Actor-Network Theory

Abstract

Knowledge on the social web presupposes gathering information about its current and potential users and document their relationships, interests and needs. A recent branch of sociology, the Actor-Network Theory (ANT), states that relations among human and nonhuman actors are equally important to understand social phenomena. Since scientists are potential users of huge computational support, their communities provide relevant cases for domain characterization and software design. This paper investigates the possibilities of using ANT to characterize a real instance of those social networks. The active role of nonhuman actors allows us to trace the relations based on material clues left behind by the actors, and also to bring forth features to be explored by the social software. The results of a structural study offer a graphical representation that allows quantitative and qualitative analysis of the social network, while the temporal evolution case study suggests that cyclic associations are more likely to persist. These outcomes may inform a better design of Web 2.0 systems for those communities.