Applied Network Science最新文献_第9页

Parameterizing network graph heterogeneity using a modified Weibull distribution. 使用改进的威布尔分布参数化网络图的异质性。

IF 2.2

Applied Network Science Pub Date : 2023-01-01 DOI: 10.1007/s41109-023-00544-9

Sinan A Ozbay, Maximilian M Nguyen

引用次数: 3

Impact of network centrality and income on slowing infection spread after outbreaks. 网络中心性和收入对疫情后减缓感染传播的影响。

IF 2.2

Applied Network Science Pub Date : 2023-01-01 DOI: 10.1007/s41109-023-00540-z

Shiv G Yücel, Rafael H M Pereira, Pedro S Peixoto, Chico Q Camargo

{"title":"Impact of network centrality and income on slowing infection spread after outbreaks.","authors":"Shiv G Yücel, Rafael H M Pereira, Pedro S Peixoto, Chico Q Camargo","doi":"10.1007/s41109-023-00540-z","DOIUrl":"https://doi.org/10.1007/s41109-023-00540-z","url":null,"abstract":"The COVID-19 pandemic has shed light on how the spread of infectious diseases worldwide are importantly shaped by both human mobility networks and socio-economic factors. However, few studies look at how both socio-economic conditions and the complex network properties of human mobility patterns interact, and how they influence outbreaks together. We introduce a novel methodology, called the Infection Delay Model, to calculate how the arrival time of an infection varies geographically, considering both effective distance-based metrics and differences in regions' capacity to isolate-a feature associated with socio-economic inequalities. To illustrate an application of the Infection Delay Model, this paper integrates household travel survey data with cell phone mobility data from the São Paulo metropolitan region to assess the effectiveness of lockdowns to slow the spread of COVID-19. Rather than operating under the assumption that the next pandemic will begin in the same region as the last, the model estimates infection delays under every possible outbreak scenario, allowing for generalizable insights into the effectiveness of interventions to delay a region's first case. The model sheds light on how the effectiveness of lockdowns to slow the spread of disease is influenced by the interaction of mobility networks and socio-economic levels. We find that a negative relationship emerges between network centrality and the infection delay after a lockdown, irrespective of income. Furthermore, for regions across all income and centrality levels, outbreaks starting in less central locations were more effectively slowed by a lockdown. Using the Infection Delay Model, this paper identifies and quantifies a new dimension of disease risk faced by those most central in a mobility network.","PeriodicalId":37010,"journal":{"name":"Applied Network Science","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9951146/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10872656","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

The persistent homology of genealogical networks. 宗谱网络的持久同源性。

IF 2.2

Applied Network Science Pub Date : 2023-01-01 DOI: 10.1007/s41109-023-00538-7

Zachary M Boyd, Nick Callor, Taylor Gledhill, Abigail Jenkins, Robert Snellman, Benjamin Webb, Raelynn Wonnacott

{"title":"The persistent homology of genealogical networks.","authors":"Zachary M Boyd, Nick Callor, Taylor Gledhill, Abigail Jenkins, Robert Snellman, Benjamin Webb, Raelynn Wonnacott","doi":"10.1007/s41109-023-00538-7","DOIUrl":"https://doi.org/10.1007/s41109-023-00538-7","url":null,"abstract":"Genealogical networks (i.e. family trees) are of growing interest, with the largest known data sets now including well over one billion individuals. Interest in family history also supports an 8.5 billion dollar industry whose size is projected to double within 7 years [FutureWise report HC-1137]. Yet little mathematical attention has been paid to the complex network properties of genealogical networks, especially at large scales. The structure of genealogical networks is of particular interest due to the practice of forming unions, e.g. marriages, that are typically well outside one's immediate family. In most other networks, including other social networks, no equivalent restriction exists on the distance at which relationships form. To study the effect this has on genealogical networks we use persistent homology to identify and compare the structure of 101 genealogical and 31 other social networks. Specifically, we introduce the notion of a network's persistence curve, which encodes the network's set of persistence intervals. We find that the persistence curves of genealogical networks have a distinct structure when compared to other social networks. This difference in structure also extends to subnetworks of genealogical and social networks suggesting that, even with incomplete data, persistent homology can be used to meaningfully analyze genealogical networks. Here we also describe how concepts from genealogical networks, such as common ancestor cycles, are represented using persistent homology. We expect that persistent homology tools will become increasingly important in genealogical exploration as popular interest in ancestry research continues to expand.","PeriodicalId":37010,"journal":{"name":"Applied Network Science","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9950181/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9353129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Network embedding aided vaccine skepticism detection. 网络嵌入辅助疫苗怀疑性检测。

IF 1.3

Applied Network Science Pub Date : 2023-01-01 Epub Date: 2023-02-16 DOI: 10.1007/s41109-023-00534-x

Ferenc Béres, Tamás Vilmos Michaletzky, Rita Csoma, András A Benczúr

引用次数: 0

Fraud, corruption, and collusion in public procurement activities, a systematic literature review on data-driven methods 公共采购活动中的欺诈、腐败和勾结，关于数据驱动方法的系统文献综述

IF 2.2

Applied Network Science Pub Date : 2022-12-15 DOI: 10.1007/s41109-022-00523-6

Marcos S. Lyra, B. Damásio, Flávio L. Pinheiro, F. Bação