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network science approach for identifying disruptive elements of an airline

Data science and Management 2023年第2期6卷 110-121页

作者： Vinod Kumar Chauhan Anna Ledwoch Alexandra Brintrup Manuel Herrera Vaggelis Giannikas Goran Stojkovic Duncan Mcfarlane Institute for Manufacturing University of CambridgeCambridgeCB30FSUK Department of Engineering science University of OxfordOxfordOX13PJUK School of Management University of BathBathBA27AZUK The Boeing Company Arlington22202US

Currently,flight delays are common and they propagate from an originating flight to connecting flights,leading to large disruptions in the overall *** disruptions cause massive economic losses,affect airlines’reputations,waste passengers’time and money,and directly impact the *** study adopts a network science approach for solving the delay propagation problem by modeling and analyzing the flight schedules and historical operational data of an *** aim to determine the most disruptive airports,flights,flightconnections,and connection types in an airline *** elements are influential or critical entities in an airline *** are the elements that can either cause(airline schedules)or have caused(historical data)the largest disturbances in the *** airline can improve its operations by avoiding delays caused by the most disruptive *** proposed network science approach for disruptive element analysis was validated using a case study of an operating *** analysis indicates that potential disruptive elements in a schedule of an airline are also actual disruptive elements in the historical data and they should be considered to improve *** airline network exhibits small-world effects and delays can propagate to any part of the network with a minimum of four delayed ***,we observed that passenger connections between flights are the most disruptive connection ***,the proposed methodology provides a tool for airlines to build robust flight schedules that reduce delays and propagation.

关键词： Air transport Flight delays Airline disruptions Delay propagation network science

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Evolution of airports from a network perspective--An analytical concept

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Chinese Journal of Aeronautics 2017年第2期30卷 513-522页

作者： Mark Azzam German Aerospace Center -DLR 53227 Bonn Germany

Analyzing airports＇ role in global air transportation and monitoring their development over time provides an additional perspective on the dynamics of network *** order to understand the different roles airports can play in the network an integrated and multidimensional approach is ***,an approach to airport classification through hierarchical clustering considering several parameters from network theory is presented in this *** applying a 29 year record of global flight data and calculating the conditional transition probabilities the results are displayed as an evolution graph similar to a discrete-time Markov *** this analytical concept the meaning of airports is analyzed from a network perspective and a new airport taxonomy is *** presented methodology allows tracking the development of airports from certain categories into others over *** show that airports of equal classes run through similar stages of development with a limited number of alternatives,indicating clear evolutionary *** from giving an overview of the results the paper illustrates the exact data-driven approach and suggests an evaluation *** methodology can help the public and industry sector to make informed strategy decisions when it comes to air transportation infrastructure.

关键词： Airport classification Air transportation Cluster analysis Complexity science network development network science

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Small World Effects in a Harmonious Unifying Hybrid Preferential Model networks

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Communications in Theoretical Physics 2007年第2X期48卷 377-383页

作者： FANG Jin-Qing BI Qiao LI Yong LU Xin-Biao LIU Qiang China Institute of Atomic Energy P.O. Box 275-81 Beijing 102413 China

Small worm effects in the harmonious unifying hybrid preferential model （HUHPM） networks are studied both numerically and analytically. The idea and method of the HUHPM is applied to three typical examples of unweighted BA model, weighted BBV model, and the TDE rnodel, so-called HUHPM-BA, HUHPM-BBV and HUHPM- TDE networks. Comparing the HUHPM with current typical models above, it is found that the HUHPM networks has the smallest average path length and the biggest average clustering coefficient. The results demonstrate that the HUHPM is more suitable not only for the un-iveighted models but also for the weighted models.

关键词： harmonious unifying hybrid preferential model small world effect network science

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HITS hits art

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Blockchain(Research and Applications) 2021年第4期2卷 64-70页

作者： Massimo Franceschet Department of Mathematics Computer Science and PhysicsUniversity of UdineVia delle Scienze 206Udine33100Italy

The blockchain art market is partitioned around the roles of artists and collectors and highly concentrated among a few prominent *** hence propose to adapt Kleinberg's authority/hub HITS(Hyperlink-Induced Topic Search)method to rate artists and collectors in the art *** seems a reasonable choice since the original method deftly defines its scores in terms of a mutual recursive relationship between authorities/artists—the miners of information/art,and hubs/collectors—the assemblers of such information/*** evaluated the proposed method on the collector-artist network of SuperRare gallery,the major crypto art *** found that the proposed artist and collector metrics are weakly correlated with other networks science metrics like degree and *** hints at the possibility of coupling different measures in order to profile active users of the gallery and suggests investment strategies with different risk/reward ratios for collectors as well as marketing strategies with different targets for artists.

关键词： Blockchain Non-fungible tokens Crypto art network science Centrality measures

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Infrastructure of Scientometrics: The Big and network Picture

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Journal of Data and Information science 2019年第4期4卷 1-12页

作者： Jinshan Wu School of Systems science Beijing Normal University

A network is a set of nodes connected via edges,with possibly directions and weights on the ***,in a multi-layer network,the nodes can also be *** this perspective,based on previous studies,we argue that networks can be regarded as the infrastructure of scientometrics in the sense that networks can be used to represent scientometric *** the task of answering various scientometric questions related to this data becomes an algorithmic problem in the corresponding network.

关键词： network science Scientometrics

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Identifying spreading influence nodes for social networks

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Frontiers of Engineering Management 2022年第4期9卷 520-549页

作者： Yang OU Qiang GUO Jianguo LIU Research Center of Complex Systems science University of Shanghai for Science and TechnologyShanghai 200093China Institute of Accounting and Finance Shanghai University of Finance and EconomicsShanghai 200433China

The identification of spreading influence nodes in social networks,which studies how to detect important individuals in human society,has attracted increasing attention from physical and computer science,social science and economics *** identification algorithms of spreading influence nodes can be used to evaluate the spreading influence,describe the node’s position,and identify interaction *** review summarizes the recent progress about the identification algorithms of spreading influence nodes from the viewpoint of social networks,emphasizing the contributions from physical perspectives and approaches,including the microstructure-based algorithms,community structure-based algorithms,macrostructure-based algorithms,and machine learning-based *** introduce diffusion models and performance evaluation metrics,and outline future challenges of the identification of spreading influence nodes.

关键词： complex network network science spreading influence machine learning

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network Approaches to Substance Use and HIV/Hepatitis C Risk among Homeless Youth and Adult Women in the United States: A Review

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Health 2016年第12期8卷 1143-1165页

作者： Kirk Dombrowski Kelley Sittner Devan Crawford Melissa Welch-Lazoritz Patrick Habecker Bilal Khan Department of Sociology University of Nebraska-Lincoln Lincoln USA Department of Sociology Oklahoma State University Stillwater USA REACH Lab University of Nebraska-Lincoln Lincoln USA

During the United States economic recession of 2008-2011, the number of homeless and unstably housed people in the United States increased considerably. Homeless adult women and unaccompanied homeless youth make up the most marginal segments of this population. Because homeless individuals are a hard to reach population, research into these marginal groups has traditionally been a challenge for researchers interested in substance abuse and mental health. network analysis techniques and research strategies offer means for dealing with traditional challenges such as missing sampling frames, variation in definitions of homelessness and study inclusion criteria, and enumeration/population estimation procedures. This review focuses on the need for, and recent steps toward, solutions to these problems that involve network science strategies for data collection and analysis. Research from a range of fields is reviewed and organized according to a new stress process framework aimed at understanding how homeless status interacts with issues related to substance abuse and mental health. Three types of network innovation are discussed: network scale-up methods, a network ecology approach to social resources, and the integration of network variables into the proposed stress process model of homeless substance abuse and mental health. By employing network methods and integrating these methods into existing models, research on homeless and unstably housed women and unaccompanied young people can address existing research challenges and promote more effective intervention and care programs.

关键词： network science Homeless Women Homeless Youth Stress Process Models network Ecology Racial/Ethnic Health Disparities

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GatherTweet: A Python Package for Collecting Social Media Data on Online Events

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Journal of Computer and Communications 2023年第2期11卷 172-193页

作者： Claudia Kann Sarah Hashash Zachary Steinert-Threlkeld R. Michael Alvarez Department of Humanities and Social sciences California Institute of Technology Pasadena USA Luskin School of Public Affairs University of California Los Angeles Los Angeles USA

Social media plays a crucial role in the organization of massive social movements. However, the sheer quantity of data generated by the events as well as the data collection restrictions that researchers encounter, leads to a series of challenges for researchers who want to analyze dynamic public discourse and opinion in response to and in the creation of world events. In this paper we present gatherTweet, a Python package that helps researchers efficiently collect social media data for events that are composed of many decentralized actions (across both space and time). The package is useful for studies that require analysis of the organizational or baseline messaging before an action, the action itself, and the effects of the action on subsequent public discourse. By capturing these aspects of world events gatherTweet enables the study of events and actions like protests, natural disasters, and elections.

关键词： Data science Movements Social Media Data Twitter network science Data Mining Python

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