Studies of social networks since the 20th century have revolved around the mapping of connections between humans. We have come a long way from early studies which involve, in the main, direct observation of the participants themselves.
Online social networks (OSNs) such as Twitter first enabled large scale research in the 2000s; which necessitated a shift in techniques and processing power needed for analysis. Calculations of network statistics — which were hitherto able to be performed on the entirety of the network — had to be adapted to modern networks which are awash with nodes and vertices totalling millions.
With Twitter’s recent pivoting to a “pay-to-play” paradigm, the dearth of data, once easily made available to researchers, has triggered a rethink of the questions we can ask, and methods we can use.
In this talk, I will highlight these, and other, challenges – from my experience and that of peers in the field of social network analysis. I will posit three open challenges (or, opportunities!) with OSNs (“three A’s”) that are left wanting for more answers, which we as interdisciplinary researchers are positioned to answer.
Firstly: the shift from OSNs from small-scale symmetric to large-scale asymmetric. Second: the algorithms powering social networks with an “optimising for engagement” paradigm, which need not be in the interests of end users. Third: Audacious (or adverse) design choices, designed again to promote engagement — from the red dot on one’s notifications, to the relative ease of mindlessly resharing content — working in tandem with the prior two challenges.
I will highlight current approaches used in the field: techniques which allow us to look at the three A’s, to supplement extant research, from existentialism to ethnography. Then, I will review examples of how philosophers and data/computer scientists can co-create techniques to make inquiry accessible to allied researchers. Finally, with the dearth of free data sources, I explore ways to further research on OSNs.