The importance of individuals and groups in networks is modeled by various centrality measures. Additionally, Freeman’s centralization is a way to normalize any given centrality or group centrality measure, which enables us to compare individua...
Networks are useful to describe the structure of many complex systems. Often, understanding these systems implies the analysis of multiple interconnected networks simultaneously, since the system may be modelled by more than one type of interaction....
The centrality of religiosity scale (CRS) is a measure of the importance of religious constructs in personality. The Polish CRS has been applied in more than 40 published studies on the psychology of religion, with over 18,000 total participants. How...
Developing a tailor-made centrality measure for a given task requires domain- and network-analysis expertise, as well as time and effort. Thus, automatically learning arbitrary centrality measures for providing ground-truth node scores is an importan...
This paper describes an adaptation of the Centrality of Religiosity Scale to the Buddhist religious tradition (CBRS) and a validation in Vietnam. The sample included data from 421 Vietnamese Buddhists (300 females, 121 males), aged 17 to 71 years (
The Centrality of Religiosity Scale (CRS) is a measure of the centrality, importance or salience of religious meanings in personality that has been applied yet in more than 100 studies in sociology of religion, psychology of religion and religious st...
The present intervention study tested the following hypothesis: the influence of one’s personal religious construct system is more intense and broader on therapy outcome if it stays central within the personality or becomes more central through...
The centralization of the global DNS ecosystem may accelerate the creation of an oligopoly market, thereby, increasing the risk of a single point of failure and network traffic manipulation. Earlier studies have revealed the level of centralization i...
We propose a new centrality measure based on a self-adaptive epidemic model characterized by an endogenous reinforcement mechanism in the transmission of information between nodes. We provide a strategy to assign to nodes a centrality score that depe...
The importance of a place can be assessed via an analysis of its centrality. However, although central place research has a long history, there is no generally accepted theoretical base, leading to continuous debates about the core elements of centra...
This article combines the traditional definition of portfolio risk with minimum-spanning-tree-based “interconnectedness risk” to improve equal risk contribution portfolio performance. We use betweenness centrality to measure an asset&rsqu...
Betweenness centrality evaluates the importance of nodes and edges in networks and is one of the most pivotal indices in complex network analysis; for example, it is widely used in centrality ordering, failure cascading modeling, and path planning. E...
Graphs can be found in almost every part of modern life: social networks, road networks, biology, and so on. Finding the most important node is a vital issue. Up to this date, numerous centrality measures were proposed to address this problem; howeve...
In light of the fact that existing centrality indexes disregard the influence of dynamic characteristics and lack generalizability due to standard diversification, this study investigates dynamic survivability centrality, which enables quantification...
When applying traditional criteria of Roman urbanism, several settlements in the province of Moesia are not recognised as parts of the urban network. To avoid this, previous criteria of urbanism should be revised. This paper suggests revisions, which...
Centrality is one of the most studied concepts in network analysis. Despite an abundance of methods for measuring centrality in social networks has been proposed, each approach exclusively characterizes limited parts of what it implies for an actor t...
In this paper, we present a new method to measure the nodes’ centrality in a multilayer network. The multilayer network represents nodes with different relations between them. The nodes have an initial relevance or importance value. Then, the n...
Information cascades refer to a type of learning behavior in social networks where individuals make decisions by observing the actions of others, rather than relying solely on their own private information. Network centrality, which measures the rela...
Measuring centrality has recently attracted increasing attention, with algorithms ranging from those that simply calculate the number of immediate neighbors and the shortest paths to those that are complicated iterative refinement processes and objec...
This study investigates the role of urban centrality in shaping urban form and function, with a specific focus on the city of Hail, Saudi Arabia as a representative case. Urban centrality—defined as the spatial and functional concentration of e...
We introduce distance entropy as a measure of homogeneity in the distribution of path lengths between a given node and its neighbours in a complex network. Distance entropy defines a new centrality measure whose properties are investigated for a vari...
One of the common methods to measure the centrality of nucleus-nucleus collision events consists of detecting forward spectator neutrons. Because of non-monotonic dependence of neutron numbers on centrality, other characteristics of spectator matter...
Biological networks are often large and complex, making it difficult to accurately identify the most important nodes. Node prioritization algorithms are used to identify the most influential nodes in a biological network by considering their relation...
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It is of great significance to study the interactive relationship between urban transportation and land use for promoting the healthy and sustainable development of cities. Taking Jinan, China, as an example, this study explored the interactive relat...
Geographical centrality is an evolving concept that differs from one perspective to another at different stages. The unprecedented development of high-speed information and transportation networks has highlighted the important role of space of flows...
One of the most important problems in complex networks is the location of nodes that are essential or play a main role in the network. Nodes with main local roles are the centers of real communities. Communities are sets of nodes of complex networks...
Influential nodes are rare in social networks, but their influence can quickly spread to most nodes in the network. Identifying influential nodes allows us to better control epidemic outbreaks, accelerate information propagation, conduct successful e...
Analyzing the structure of a social network helps in gaining insights into interactions and relationships among users while revealing the patterns of their online behavior. Network centrality is a metric of importance of a network node in a network,...
The combinatorial problem in this paper is motivated by a variant of the famous traveling salesman problem where the salesman must return to the starting point after each delivery. The total length of a delivery route is related to a metric known as...
Access to and interaction with natural blue or green spaces is a critical factor in quality of life and overall well-being. Studies have shown that exposure to natural areas has health benefits for individuals and society. Incorporating interconnecte...
Clear and straightforward communication is a key aspect of all human activities related to crisis management. Since crisis management activities involve professionals from various disciplines using different terminology, clear and straightforward com...
In the area of network analysis, centrality metrics play an important role in defining the “most important” actors in a social network. However, nowadays, most types of networks are dynamic, meaning their topology changes over time. The connection we...
This study presents the validation of the short forms of Centrality of Religiosity Scale (CRS) in Georgia. This country offers a unique Christian orthodox context with a long-lasting religious tradition and strong affiliation to churches. Translated...
Analyzing massive graphs poses challenges due to the vast amount of data available. Extracting smaller relevant subgraphs allows for further visualization and analysis that would otherwise be too computationally intensive. Furthermore, many real data...
The stock market is an essential sub-sector in the financial area. Both understanding and evaluating the mountains of collected stock data has become a challenge in relevant fields. Data visualisation techniques can offer a practical and engaging met...
In recent decades, Bangkok has experienced substantial investments in its urban railway network, resulting in a profound transformation of the city’s landscape. This study examines the relationship between railway development and property value...
Research on Islamophobia in Switzerland, and on the role of religiosity in relation to Islamophobia, is in its infancy. Against this background, we analyzed data from an online survey conducted in Switzerland on “Xenosophia and Xenophobia in an...
We introduce a refined way to diffusely explore complex networks with stochastic resetting where the resetting site is derived from node centrality measures. This approach differs from previous ones, since it not only allows the random walker with a...
In recent decades, complex network theory has become one of the most important approaches for exploring the structure and dynamics of traffic networks. Most studies mainly focus on the static topology features of the traffic networks, and there are a...
Identifying the influential nodes in complex networks is a fundamental and practical topic at the moment. In this paper, a new centrality measure for complex networks is proposed based on two contrasting models that have their common origin in the we...
Graph energy is the energy of the matrix representation of the graph, where the energy of a matrix is the sum of singular values of the matrix. Depending on the definition of a matrix, one can contemplate graph energy, Randić energy, Laplacian energy...
In this work, we introduce an edge centrality measure for the Helmholtz equation on metric graphs, a particular flow network, based on spectral edge energy density. This measure identifies influential edges whose removal significantly changes the ene...
With the recent exponential growth in inter-regional movements of population and information, there is an urgent need for accurately measuring the connectivity and centrality of cities. This study aims to investigate the differences in centrality bet...
We live in a time dominated by interconnected networks surrounding us on all fronts. The emergence of social media platforms has driven the expansion of social networks, facilitating fast communication worldwide. Responses to content shared on these...
This paper investigates the salience of religion and the centrality of religiosity among select LGBTQs. Much consideration has been given to the identity categories of sex, gender, sexual orientation, and religion. Means (M) and standard deviations (...
Objective: The aim was to validate a Romanian version of the Centrality of Religiosity Scale (CRS 15) and to determine its psychometric properties in religious and highly religious people. Methods: A cross-sectional survey was conducted in different...
This paper presents a comprehensive review of centrality measures and their usefulness in transportation networks in the face of climate change adaptation. The focus is on understanding the importance of transportation nodes in the event of extreme w...
Link prediction plays a crucial role in identifying future connections within complex networks, facilitating the analysis of network evolution across various domains such as biological networks, social networks, recommender systems, and more. Researc...
This paper investigates the effectiveness of centrality measures for the influence maximization problem in competitive social networks (SNs). We consider a framework, which we call “I-Game” (Influence Game), to conceptualize the adoption...
Accurately predicting flight delays remains a significant challenge in the aviation industry due to the complexity and interconnectivity of its operations. The traditional prediction methods often rely on meteorological conditions, such as temperatur...
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