![]() PageRank, an algorithm used by the Google Search Engine, is another useful network metric used to identify important web-pages. However, network centrality does not capture the transitive effect of network topology and thus could underestimate or overestimate the importance of nodes. Alderson and Beckfield examined interactions among multinational enterprises and their subsidiaries across cities, using out-degree centrality to show the influence of each city on the world economy, in-degree centrality to show each city’s ability to attract investment from other cities, closeness centrality to show each city’s independence, and betweenness centrality to show the potential of each city to act as a bridge, brokering interactions (investment flow) among cities or subgroups of cities. The concept of network centrality has often been used to explore locational characteristics in connection with interactions within the network. Previous studies have used network metrics to retrieve information from the real world. These studies have focused on the network positions of connected spatial features and on the vulnerabilities and strengths of locations within networks. In summary, these studies created topological networks of spatial features and used them to explore geographical connectivity and structures. , and Scholz used airline networks to explore the concentration of air transportation and find hubs or hot spots. created an inter-port network to measure the vulnerability of each port. created a street network and used this network to explain the relative importance of different locations with respect to land-use. , and Jiang and Jia created a street-to-street topological network to elucidate human movement on streets. created a commuting network to determine accessibility. El-Geneidy and Levinson and Reggiani et al. Alderson and Beckfield created a world-city network in which the nodes were world cities and the links were formed by interactions among multinational enterprises and their subsidiaries in different cities they explored the economic status and position of each city within the network. To explore and understand spatial features and the structures within them, recent studies have adapted network topological analysis frameworks to geography. ![]() Analysis of the structure of a flow network can be used to elucidate interactions among these features. The links are formed by connections or volumes of flow between locations, for example, commuting volumes between regions or volumes of air traffic between airports. The nodes represent spatial features that can be indicated as points (e.g., ports, airports, or buildings) or areas (e.g., countries, cities, or regions). A network approach, which simplifies geographic settings into combinations of nodes and links, emphasizes the connectivity and relationships among spatial features. The elements of a terrestrial system are connected, and their spatial relationships should not be ignored. Geographers extend this fundamental concept to connected spatial features located in finite geo-spaces. Ecologists believe that there is one ecosphere for all living organisms, that what affects one affects all, and that everything is connected to everything else. The real world contains extensive connections. This implies that geographic proximity remains a key factor in human mobility. In comparing location attractiveness and distance decay, we conclude that the concentration of human movement is largely determined by the distance decay. Our findings indicate that in both intercity and within-city settings the proposed algorithms more effectively capture the spatial locations where people reside than traditional commonly-used network metrics. The objective of the present study is to propose two geographically modified PageRank algorithms-Distance-Decay PageRank (DDPR) and Geographical PageRank (GPR)-that incorporate geographic considerations into PageRank algorithms to identify the spatial concentration of human movement in a geospatial network. However, geographic considerations, including proximity and location attractiveness, are ignored in most network metrics. The PageRank algorithm, a network metric, is often used to help identify important locations where people or automobiles concentrate in the geographical literature. Topological networks of spatial features are used to explore geographical connectivity and structures. ![]() A network approach, which simplifies geographic settings as a form of nodes and links, emphasizes the connectivity and relationships of spatial features.
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