Spatio-temporal evolution and influencing factors of geopolitical relations among Arctic countries based on news big data

Abstract

Global warming has caused the Arctic Ocean ice cover to shrink. This endangers the environment but has made traversing the Arctic channel possible. Therefore, the strategic position of the Arctic has been significantly improved. As a near-Arctic country, China has formulated relevant policies that will be directly impacted by changes in the international relations between the eight Arctic countries (regions). A comprehensive and real-time analysis of the various characteristics of the Arctic geographical relationship is required in China, which helps formulate political, economic, and diplomatic countermeasures. Massive global real-time open databases provide news data from major media in various countries. This makes it possible to monitor geographical relationships in real-time. This paper explores key elements of the social development of eight Arctic countries (regions) over 2013-2019 based on the GDELT database and the method of labeled latent Dirichlet allocation. This paper also constructs the national interaction network and identifies the evolution pattern for the relationships between Arctic countries (regions). The following conclusions are drawn. (1) Arctic news hotspot is now focusing on climate change/ice cap melting which is becoming the main driving factor for changes in geographical relationships in the Arctic. (2) There is a strong correlation between the number of news pieces about ice cap melting and the sea ice area. (3) With the melting of the ice caps, the social, economic, and military activities in the Arctic have been booming, and the competition for dominance is becoming increasingly fierce. In general, there is a pattern of domination by Russia and Canada.

Analysis of a Multiple Traffic Flow Network’s Spatial Organization Pattern Recognition Based on a Network Map

“…However, the findings are subject to certain limitations. Outside the city, urban networks are mainly constructed separately using highway [7,8], railway [9][10][11][12], aviation [13][14][15], and flight data. Due to differences in efficiency and experience among different modes of transportation, their spatial patterns and spatial organization models are diverse.…”