The author proposes a stronger embedding of SN systems in geographic space. In their framework, a node (geospatial agent) in a SN has its geolocation information formalised in the concept of an ‘anthropospace’. Unlike previous descriptions of human movement (e.g. life paths, anchor points), the anthropospace is a fluid concept which can refer to points, lines, areas, probability clouds associated with a social agent’s ‘activities’. I think this terminology is compelling in its universality, but may (as emphasised by the author) present challenges in a GIS setting. For instance, how should GIS deal with nodes that have different types/ scales of anthropospace?
The idea of non-Euclidean geometries and network analyses are not new in Geography. For instance, the time it takes for a human agent to traverse geographic space forms a highly variable non-Euclidean metric space over the Earth, which might be constrained by a transport network or the individual’s characteristics. The additional difficulty with SNs is dealing with the transient/ ambiguously defined geolocations of nodes. To address this, the concept of ’social flows’ are introduced to signify social connections in geographic space. The calculation of a ‘socially-bounded’ Scotland was a particularly amusing (/troubling) example. Of course, social flow can only be derived from proxies for social connection (like phone calls).
I’m not convinced Andris’s system represents a definitive framework for resolving SN and GIS, but it does offer significant insights and examples. Further work would be necessary to persuade readers that the suggested typologies are exhaustive, non-arbitrary, and widely useful. Would a technical fix (making GIS software more SN compatible) solve this problem? I agree with the author that a conceptual understanding also needs to be advanced.
-slumley