LBSN Data and the Social Butterfly Effect (Vision Paper)

Abstract

LBSN data are well-suited for research questions and perspectives on social or spatial phenomena. Researchers often subset large LBSN datasets into different social networks (using snowball sampling), temporal or spatial granularities, to test for statistical patterns. Yet, researchers lack a way to examine how human interpersonal behavior results in digital traces of geolocated social events, although macro global flows of movement and communication are built from micro individual human intentions. To help navigate between the individual mind and the resultant big LBSN data that researchers use to understand society and space, I list a 14-tier scale of connectivity typologies. Each step can provide different a perspective of a single LBSN dataset. This scale can illustrate how perturbations at one level affect another level. E.g. How will reported escalating rates of autism affect the future network of connectivity between global cities? Will a change in migration policy strain emotional ties between an international family? The scale allows us to track changes at different levels between micro-, meso- and macro-scale social-spatial phenomena in a computationally-friendly way.