Core–periphery structure
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Core–periphery structure is a network theory model.
Models of core–periphery structures
[edit]There are two main intuitions behind the definition of core–periphery network structures; one assumes that a network can only have one core, whereas the other allows for the possibility of multiple cores. These two intuitive conceptions serve as the basis for two modes of core–periphery structures.
Discrete model
[edit]This model assumes that there are two classes of nodes. The first consists of a cohesive core sub-graph in which the nodes are highly interconnected, and the second is made up of a peripheral set of nodes that is loosely connected to the core. In an ideal core–periphery matrix, core nodes are adjacent to other core nodes and to some peripheral nodes while peripheral nodes are not connected with other peripheral nodes (Borgatti & Everett, 2000, p. 378). This requires, however, that there be an a priori partition that indicates whether a node belongs to the core or periphery.

Continuous model
[edit]This model allows for the existence of three or more partitions of node classes. However, including more classes makes modifications to the discrete model more difficult.[clarification needed] Borgatti & Everett (1999) suggest that, in order to overcome this problem, each node be assigned a measure of ‘coreness’ that will determine its class. Nevertheless, the threshold of what constitutes a high ‘coreness’ value must be justified theoretically.
Discussion
[edit]Hubs are commonly found in empirical networks and pose a problem for community detection as they usually have strong ties to many communities. Identifying core–periphery structures can help circumvent this problem by categorizing hubs as part of the network's core (Rombach et al., 2014, p. 160). Likewise, though all core nodes have high centrality measures, not all nodes with high centrality measures belong to the core. It is possible to find that a set of highly central nodes in a graph does not make an internally cohesive subgraph (Borgatti & Everett, 2000)...
Uses in economics
[edit]The concept was first introduced into economics as "centre-periphery" by Raúl Prebisch in the 1950s, but the origin of the idea could ultimately be traced back to Thünen's Isolated State (1826).[1] However, the qualitative notion that social networks can have a core–periphery structure has a long history in disciplines such as sociology, international relations (Nemeth & Smith, 1985), and economics (Snyder & Kick, 1979). Observed trade flows and diplomatic ties among countries fit this structure. Paul Krugman (1991) suggests that when transportation costs are low enough manufacturers concentrate in a single region known as the core and other regions (the periphery) limit themselves to the supply of agricultural goods.
The "centre-periphery" model was classically developed by John Friedmann in 1966 in his book Regional Development Policy: A Case Study of Venezuela.[2]
For regional relations and variations in Russia Professor Natalia Zubarevich proposed an extension of the centre-periphery model and is known as the author of the "theory of four Russias".[3] According to Zubarevich, the different speed of social modernisation is more accurately explained by the centre-periphery model. The entire population of the country can be divided into three roughly equal parts - about a third of citizens in each. The underdeveloped republics, where 6% of the country's population lives - this "fourth" Russia has its own specific features.[4][5][6] According to the concept, "First Russia" is the cities with millions of inhabitants, i.e. the most modernised and economically developed territories. "Second Russia" are medium-sized cities with a pronounced industrial profile. "Third Russia" - small towns, workers' settlements, rural areas. Compared to "first" and "second Russia" - this is a deep periphery in terms of the quality of socio-economic life. The "fourth Russia" is made up of the national republics of the Caucasus, as well as the south of Siberia (Tuva, the Altai Republic). These territories also represent a periphery, but a specific one: the demographic transition has not been completed here, urbanisation is in its infancy, and patriarchal-clan principles are still strong in society.[7] Monoprofile towns (monotowns) are the most unstable part of the "second Russia".[8]
See also
[edit]- World-systems theory
- Core countries
- Semi-periphery countries
- Periphery countries
- Degeneracy (graph theory)
References
[edit]- ^ Rama, J.; Hall, J. (2021). "Raúl Prebisch and the evolving uses of 'centre-periphery'in economic analysis". Review of Evolutionary Political Economy. 2 (2): 315–332.
- ^ ISBN 978-0262060134
- ^ https://trends.rbc.ru/trends/social/64e30dd89a7947b8f0158fe1
- ^ https://www.vedomosti.ru/newspaper/articles/2013/09/24/chetyre-rossii-chto-dalshe
- ^ https://www.vedomosti.ru/opinion/articles/2011/12/30/chetyre_rossii
- ^ https://www.vedomosti.ru/authors/natalya-zubarevich
- ^ https://trends.rbc.ru/trends/social/64e30dd89a7947b8f0158fe1
- ^ https://www.vedomosti.ru/opinion/articles/2011/12/30/chetyre_rossii
- Borgatti, S. P., & Everett, M. G. (1999). Models of core /periphery structures. Social Networks, 21, 375–395. doi:10.1016/S0378-8733(99)00019-2
- Krugman, P.R. (1991), Increasing returns and economic geography, Journal of Political Economy 99, 483–499.
- Nemeth, R. J., & Smith, D. A. (1985). International trade and world-system structure: A multiple network analysis (No. 8).
- Rombach, M. P., Porter, M. A., Fowler, J. H., & Mucha, P. J. (2014). Core–periphery structure in Networks. SIAM J. Appl. Math., 74(1), 167–190.
- Snyder, D., & Kick, E. L. (1979). Structural position in the world system and economic growth, 1955–1970: A multiple-network analysis of transnational interactions. American Journal of Sociology, 84, 1096–1126.
- Wallerstein, I. (1978). World-system analysis: theoretical and interpretative issues. World-System Analysis: Theory and Methodology, 91-103.
- Zhang, X., Martin, T., & Newman, M. E. J. (n.d.). Identification of core–periphery structure in networks, 1–10.