Authority Centrality Research Articles

Analysis of tourism destination centrality and structural properties of tourism system: Complex network perspective

ourism has become a new way of living with the living standard development. This study analyses the tourism destination centrality and spatial patterns of the tourism system using complex network analysis. An analysis of 245 destinations in the South of Thailand has found that the network has a low network density, large average path length and low clustering coefficient. Some a small number of high-degree destinations connect to each other, while most connect to others with a low degree. The network comprises 18 subnetworks that destinations densely connect to others in the same subnetwork but sparsely connect to others in different ones. Destinations play different roles in the network based on which a centrality measure is used, degree, betweenness and closeness centrality. 31 destinations with high hub and authority centrality are the centers playing as hubs of the network. The study’s findings draw implications for the sector.

Regional Comprehensive Economic Partnership (RCEP): Evaluation of Trade Relations Between Member Countries Using the Social Network Analysis Method

The Regional Comprehensive Economic Partnership (RCEP) agreement was signed in 2020 as a giant free trade agreement signed by 15 countries, including China. In this context, the RCEP agreement is the world's largest free trade agreement in terms of GDP and trade volume. In this study, commercial relations between RCEP countries between 2012 (the year when negotiations of the RCEP agreement began) and 2021 were examined using social network analysis. In the analyses, export values of RCEP countries to each other were used and the data were obtained from Trade Map. In the study, social network analyzes for the years 2012, 2015, 2018 and 2021 were analyzed using the Ucinet program, while trade networks were visualized with the Gephi program. For social network analyses, basic ego network indicators, degree centrality values, hub and authority centrality values and eigenvector values were calculated. As a result of the analysis, it is seen that the hub and authority country in trade between RCEP countries is China for all four years (2012, 2015, 2018 and 2021). On the other hand, it has been determined that China's most important trade partners are Japan and South Korea. Additionally, the development in Vietnam's trade level during this period is remarkable.

Who are the key players? Listeners vs spreaders vs others.

The literature on social learning examines how people learn from their neighbors and reach a consensus. The DeGroot social learning model describes the social learning process as one in which people form their opinions by taking a weighted average of their neighbors' opinions. In the model, the influence structure is represented by a single matrix. In this paper, we empirically identify the role of the hub and authority centralities based on this matrix using data on microfinance adoption in rural Indian villages. Controlling for other well-known centrality measures, authority centrality is positively associated with final adoption rates in the villages, but hub centrality is not. Furthermore, we find that authority centrality is the most informative variable predicting microfinance diffusion success from LASSO regressions.

Temporal dynamics of faculty hiring in mathematics

University faculty hiring networks are known to be hierarchical and to exacerbate various types of inequity. Still, a detailed, historical understanding of hiring dynamics lacks in many academic fields. We focus on the field of mathematics, analyzing over 120,000 records from 150 institutions over seven decades to elucidate the temporal dynamics of hiring doctoral-granting (DG) faculty at the individual and departmental levels. We demonstrate that the disparity between the number of mathematics Ph.D.s awarded and the number of DG faculty positions filled has grown over time. Even institutions with the best records of DG faculty placement have experienced a temporal decline in the probability of their graduates obtaining a DG faculty position. By quantifying the mathematical prestige of each department with a network statistic, authority centrality, we find an approximately linear relationship between the log of the prestige of one’s Ph.D. institution and the log of the probability of obtaining a faculty position. Moreover, we observe associations suggesting that the probability of DG faculty placement has decreased over time and is smaller for women than for men. On the departmental level, a group of 14 elite departments dominated the authority centrality of the entire network between 1950 and 2019. Strikingly, one department within this elite group increased its centrality scores consistently, which hints at the possibility for a department to improve its prestige. This analysis highlights the challenges of transitioning from Ph.D. holder to faculty member in mathematics.

Global supply and demand of medical goods in the fight against Covid-19: a network analysis

As global value chains have taken shape, the geographic concentration of production in specific centers or hubs to minimize production costs is an issue that has been raised following the onset of the Covid-19 pandemic. The criticism typically highlights how the production capacity within these global value chains is insufficient to meet the global needs for medical equipment and devices in this type of crisis. This study uses complex network analysis to examine the global trade structure of surgical masks and medical ventilators and its general patterns. The findings of this study conducted between 2019 and 2020 show that this trade structure has complex network properties and a core-periphery structure. A comparative evaluation of the results from these 2 years also reveals the economic fragility of the ventilator trade network even if it is easier to adapt urgent conditions in mask trade. In addition, according to the network analysis and the authority centrality values for 2020 the fact that the highest-ranked countries for ventilator imports are almost exclusively developed countries suggests that the trade structure might also indicate a moral deterioration. In sum, the empirical findings confirm that the structure of the current global value chains will not be immune to supply shocks during emergencies such as a pandemic.

Quantum hub and authority centrality measures for directed networks based on continuous-time quantum walks

Abstract In this article, we introduce, test and discuss three quantum methods for computing hub and authority centrality scores in directed networks. The methods are based on unitary, continuous-time quantum walks; the construction of a suitable Hermitian Hamiltonian is achieved by performing a quantum walk on the associated bipartite graph. Two methods, called CQAu and CQAw, use the same evolution operator, inspired by the classical Hyperlink-Induced Topic Search (HITS) algorithm, but with different initial states; the computation of hub and authority scores is performed simultaneously. The third method, called CQG and inspired by classical PageRank, requires instead two separate runs with different evolution operators, one for hub and one for authority scores. The methods are tested on several directed graphs with different sizes and properties; a comparison with other well-established ranking algorithms is provided. CQAw emerges as the most reliable of the three methods and yields rankings that are largely compatible with results from HITS, although CQAu and CQG also present interesting features and potential for applications.

Modeling risk contagion in the Italian zonal electricity market

Ensuring the security of stable, efficient and reliable energy supplies has intensified the interconnections between energy markets. Imbalances between supply and demand due to operational failures, congestion and other sources of risk faced by market connections can lead to a system that is vulnerable to the spread of risk and its spill-over. The main contribution of this paper is the development and estimation of a Bayesian Graphical Vector-AutoRegression and a Bayesian Graphical Structural Equation Modelling with external regressors - BG-VARX and BG-SEMX, respectively - enhancing the proper analysis of market connections.The Italian electricity market has been chosen because it is a clear example of a zonal market where risk can spread over connected zones. We estimate, for the first time, within-day and across-day zonal market interconnections with a multivariate time series of hourly prices, actual and forecast power demand and forecast wind generation over the period 2014–2019 and evaluate the dynamics and persistence of zonal market connections, examining the spread of risk in the zones of the Italian electricity market.Our findings provide an improved, accurate explanation of risk contagion, identifying the zones that are most influential in terms of hub centrality (major transmitters) and authority centrality (major recipients), respectively, for intra-day and inter-day risk propagation in the Italian electricity market. In addition, the policy implications in terms of market-monitoring are discussed.

A social network analysis of interconnections among cruise ports

Despite the dominance of the Caribbean as the leading cruise destination in the world, research that focuses on the network of cruise ports in the region is limited. To fill this research gap, the current study carried out social network analysis (SNA) to inquire into cruise port interconnections and their influence on the operation of the entire Caribbean port network. The results are summarized as follows: First, in terms of connections among ports linked to the Caribbean region, a European port and a Southampton harbor exhibit the most significant in-degree and out-degree centrality. Nevertheless, ports within the Caribbean region are still significantly represented as regards both indexes. Second, in the matter of port influence, Caribbean ports are considerably the most important with respect to hub and authority centrality (HAC), especially those located in Florida and the eastern Caribbean. This research contributes to industry through its presentation of an extended panorama of the cruise network in the region, subjecting several ports to respective analyses that describe their principal characteristics and attractiveness in the industry.

Towards Bayesian Quantification of Permeability in Micro-scale Porous Structures – The Database of Micro Networks

This article develops a Bayesian framework to quantify the absolute permeability of water in a porous structure from the geometry and clustering parameters of its underlying pore-throat network. These parameters include the network`s diameter, transivity, degree, centrality, assortativity, edge density, K-core decomposition, Kleinberg’s hub centrality scores, Kleinberg's authority centrality scores, length, and porosity. In addition, the incorporated clustering aspects of the networks have been determined with respect to several clustering criteria – edge betweenness, greedy optimization of modularity, multi-level optimization of modularity, and short random walks. As such, the article takes the first footsteps of creating a Database of Micro Networks for micro-scale porous structures, to be used as main input stream for the proposed Bayesian scheme. Doi: 10.28991/HIJ-2020-01-04-02 Full Text: PDF

Analysis of Hubs and Authorities Centrality Using Probabilistic Affinity Index (PAI) on directed-weighted graph in Social Network Analysis

Social media is a place for interaction that is connected to the internet network, Twitter is one of the most popular social media. In Twitter sometimes someone does not want to be left behind information related to a particular topic, so it is necessary to follow the user related to the topic so that the information is conveyed quickly. In this study, an analysis was carried out that applied the Hubs and Authorities Centrality method to determine user rankings and the Probabilistic Affinity Index method for weighting values. The results of authority centrality ranking can be used as a list of recommendations of a user who plays a role or has information about a particular topic and the results of centrality hub ranking can be used as a list of recommendations of a user who has an interest in a particular topic. From the testing in this study, changes in the number of other users that are related to the user have the largest average change in centrality value of 0.01188. While the change in the number of relations has the largest average change in the centrality value of 1.44087×10−9. Based on these tests, the number of other users that are related to the user has a large influence on the results of ranking compared to the number of relationships to other users.

Connection Analysis of Container Ports of the Bohai Rim Economic Circle (BREC)

The Bohai Rim Economic Circle (BREC) is an emerging economic area that has been developing rapidly and has benefited from support from the Chinese government; however, due to the unique geographic location and the late start of development, the cargo volumes and capacities of the ports in the Northern Region are comparatively smaller than the Yangtze River Delta, and the Pearl River Delta. To resolve this issue, one effective strategy is to create additional connections with ports and container ports of nearby countries. Consequently, a Social Network Analysis (SNA), including degree centrality, betweenness centrality, and hub and authority centrality, was used to analyze the route networks of the top three ports (ports of Tianjin, Qingdao, and Dalian) of BREC. A list of ports that are highly influential to these three ports in building additional connections to obtain higher cargo volumes is provided.

A bimodal social network analysis to recommend points of interest to tourists

With the progressive role of computers and their users as actors in social networks, computations alike social network analysis (SNA) are gaining in attention. This work proposes an approach based on SNA, not alone on social networks as supported by existing approaches, to estimate the tourists’ satisfaction with individual Points of Interest (POIs), and accordingly recommend those POIs or not to that tourist or its tour planning system. Moreover, instead of a common unimodal network, a bimodal tourist–reviewer network is modeled as suggested by the SNA literature given tourists and POI reviewers act as two distinct classes of entities with links between them representing their (dis)similarities. Both tourists and reviewers provide their personal attributes (like age), but reviewers then providing preferences for specific POIs, whereas tourists only preferences for certain types or categories of POIs (say archeology). Further, an algorithm for grouping into “islands” of most similar reviewers to a certain tourist given the strength of corresponding links in the bimodal network is developed. Additionally, a ranking algorithm based on in-degree or authority centrality is adopted to identify the highest ranked reviewers within the island and recommend their preferred POIs to a given tourist. If there are more than single POIs preferred per reviewer, and there remain more than requested POIs of the highly ranked reviewers to select among for recommendation, a similar centrality algorithm is applied over a reviewer–POI network with links representing a certain reviewer prefers that certain POI. The evaluation initially with an exemplary real-life experiment, and then extended to a massive online dataset from Foursquare, proves our approach as feasible in estimating the tourist’s satisfaction with individual POIs. Moreover, it is already promising since incorporating location influence remains yet our future work and might further improve its performance.

Identifying central bank liquidity super-spreaders in interbank funds networks

We model the allocation of central bank liquidity among the participants of the interbank market by using network analysis’ metrics. Our analytical framework considers that a super-spreader simultaneously excels at borrowing and lending central bank's liquidity for the whole network, as measured by financial institutions’ hub centrality and authority centrality, respectively. Evidence suggests that the Colombian interbank funds market exhibits an inhomogeneous and hierarchical network structure, akin to a core-periphery organization, in which a few financial institutions fulfill the role of central bank's liquidity super-spreaders. Our results concur with evidence from other interbank markets and other financial networks regarding the flaws of traditional direct financial contagion models based on homogeneous and non-hierarchical networks. Also, concurrent with literature on lending relationships in interbank markets, we confirm that the probability of being a super-spreader is mainly determined by financial institutions’ size, but leverage and lending concentration as well. We provide additional elements for the implementation of monetary policy and for safeguarding financial stability.

Assessing financial market infrastructures’ systemic importance with authority and hub centrality

Assessing financial market infrastructures’ systemic importance with authority and hub centrality

Identifying Central Bank Liquidity Super-Spreaders in Interbank Funds Networks

We model the allocation of central bank liquidity among the participants of the interbank market by using network analysis’ metrics. Our analytical framework considers that a super-spreader simultaneously excels at receiving (borrowing) and distributing (lending) central bank’s liquidity for the whole network, as measured by financial institutions’ hub centrality and authority centrality, respectively. Evidence suggests that the Colombian interbank funds market exhibits an inhomogeneous and hierarchical network structure, akin to a core-periphery organization, in which a few financial institutions fulfill the role of central bank’s liquidity super-spreaders. Our results concur with evidence from other interbank markets and other financial networks regarding the flaws of traditional direct financial contagion models based on homogeneous and non-hierarchical networks. Also, concurrent with literature on lending relationships in interbank markets, we confirm that the probability of being a super-spreader is mainly determined by financial institutions’ size. We provide additional elements for the implementation of monetary policy and for safeguarding financial stability.

Authority Centrality and Hub Centrality as Metrics of Systemic Importance of Financial Market Infrastructures

Network analysis has been applied to identify systemically important financial institutions after the 2008 financial crisis. Such applications have stressed the importance of centrality within the too-connected-to-fail concept. Yet, despite their well-known importance for financial stability, financial market infrastructures’ centrality has not been equally covered by literature. Some particularities of strictly hierarchical (i.e. directed and acyclic) networks may explain the inconvenience arising from using basic metrics of centrality, and may explain why assessing centrality has been limited to financial institutions’ case. This paper addresses the assessment of systemic importance for Colombian financial infrastructures by means of the estimation of authority centrality and hub centrality. Their particular advantage consists of assessing importance as the mutually reinforcing centrality arising from nodes pointing to other nodes (i.e. hubs) and from nodes being pointed-to by other nodes (i.e. authorities), even in the case of directed and acyclic networks. Results are valuable since they quantitatively support financial authorities’ efforts to (i) identify systemically important financial infrastructures under the too-connected-to-fail concept; (ii) focus the intensity of oversight, supervision and regulation where the infrastructure-related systemic impact is the greatest; and (iii) enhance their policy and decision-making capabilities.