Hidden geographies and inequalities of an online social network

Authors: Akos Jakobi*, Eotvos Lorand University
Topics: Cyberinfrastructure, Geographic Information Science and Systems, Social Geography
Keywords: online social networks, network geography, big data, social media, Hungary
Session Type: Paper
Day: 4/7/2020
Start / End Time: 10:15 AM / 11:30 AM
Room: Governors Square 17, Sheraton, Concourse Level
Presentation File: No File Uploaded

Recent age Big Data solutions provide excellent sources for analyzing spatial processes in and among cities, consequently the focal point of interest is on the huge amount of spontaneously generated digital urban footprint data, which are continuously being generated in daily interactions or simply during everyday usage of the information world. Such digital urban footprints give the chance for social sciences to uncover hidden spatial motives or to prove untested assumptions so far. By showing results of experiments on online social network data this presentation aims to highlight chances and challenges of new geography. Examples of “iWiW”, the once largest Hungarian social media site, are applied to show that interurban cyberspace networks are evolving and are structured depending on many unrevealed spatial constraints such as distance or offline geographical effects. Geolocated connectivity data in Hungary attempt to illustrate what more geography could learn from non-traditional digital urban datasets. The study aims to present results of a spatial pattern analysis as well as outcomes of studying the space-time evolution of the network with the examination of the growing number of city-to-city connections. Additionally, since large-scale networks provide non-occasional proves of strong or weak ties among networked entities, we could describe network-based inequalities among cities and regions. We tested the hypotheses that the density of network connections coincides with the social and economic development of regions and cities.

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