The Evolution of Natural Cities from the Perspective of Location-Based Social Media

Abstract

This paper examines the former location-based social medium Brightkite, over its three-year life span, based on the concept of natural cities. The term 'natural cities' refers to spatially clustered geographic events, such as the agglomerated patches aggregated from individual social media users' locations. We applied the head/tail division rule to derive natural cities, based on the fact that there are far more low-density locations than high-density locations on the earth surface. More specifically, we generated a triangulated irregular network, made up of individual unique user locations, and then categorized small triangles (smaller than an average) as natural cities for the United States (mainland) on a monthly basis. The concept of natural cities provides a powerful means to develop new insights into the evolution of real cities, because there are virtually no data available to track the history of cities across their entire life spans and at very fine spatial and temporal scales. Therefore, natural cities can act as a good proxy of real cities, in the sense of understanding underlying interactions, at a global level, rather than of predicting cities, at an individual level. Apart from the data produced and the contributed methods, we established new insights into the structure and dynamics of natural cities, e.g., the idea that natural cities evolve in nonlinear manners at both spatial and temporal dimensions.

Mapping Socials: A Voluntary Map of a Great Event in Monza Park

“…This last topic refers to, for example, to the studies of Bin Jiang and Yufan Miao in relation to the definition of "natural cities" [6]. The term refers to clustered events formalized by the use of certain social indifferent to content.…”

Geographic space as a living structure for predicting human activities using big data

“…It should be noted that the same notion of natural cities was used to refer to naturally evolved cities (Alexander 1965) rather than naturally derived cities used in this paper. However, the naturally derived cities are likely to resemble the naturally evolved cities, thus becoming an important instrument for studying city structure and dynamics; for example, the natural cities derived from the social media Brightkite check-in locations with time stamps (Jiang and Miao 2015) can be considered to be naturally evolved cities, in particular in terms of underlying mechanisms. Every natural city is a living center, and all natural cities of a country constitute an interconnected whole as a living structure (Jiang 2017).…”

“…Based on head/ tail breaks, all the edges are put into two categories: those longer than the mean, called the head; and those shorter than the mean, called the tail. The edges in the tail, being shorter edges which imply higher density locations, eventually constitute individual patches called natural cities (see the Appendix in Jiang and Miao (2015) for a tutorial). It should be noted that the same notion of natural cities was used to refer to naturally evolved cities (Alexander 1965) rather than naturally derived cities used in this paper.…”

“…(Table 2). The street nodes were extracted from OpenStreetMap for building up natural cities (Jiang and Miao 2015) as a living structure, while tweet locations are used to verify if they can be predicted by the living structure. The street nodes refer to both street junctions and ending nodes.…”

“…This makes big data unique and powerful for developing new insights into geographic forms and processes (e.g. Jiang and Miao 2015). On the other hand, big data poses enormous challenges in terms of data representation, structuring and analytics.…”