Applied Network Science最新文献_第7页

Measuring the effect of collaborative filtering on the diversity of users’ attention 衡量协同过滤对用户注意力多样性的影响

IF 2.2

Applied Network Science Pub Date : 2023-01-25 DOI: 10.1007/s41109-022-00530-7

Augustin Godinot, Fabien Tarissan

引用次数: 1

An efficient weighted network centrality approach for exploring mechanisms of action of the Ruellia herbal formula for treating rheumatoid arthritis 一种有效的加权网络中心性方法探讨鲁埃利亚草药配方治疗类风湿性关节炎的作用机制

IF 2.2

Applied Network Science Pub Date : 2023-01-24 DOI: 10.1007/s41109-022-00527-2

P. Ochieng, A. Hussain, J. Dombi, Miklós Krész

引用次数: 1

Democratizing corruption: a role structure analysis of Indonesia’s “Big Bang” decentralization 腐败民主化：印尼“大爆炸”权力下放的角色结构分析

IF 2.2

Applied Network Science Pub Date : 2023-01-24 DOI: 10.1007/s41109-023-00535-w

M. Silitonga, R. Wittek, T. Snijders, L. Heyse

引用次数: 1

Artificial benchmark for community detection with outliers (ABCD+o) 基于离群值的社区检测人工基准(ABCD+ 0)

IF 2.2

Applied Network Science Pub Date : 2023-01-13 DOI: 10.1007/s41109-023-00552-9

Bogumil Kami'nski, P. Prałat, F. Théberge

引用次数: 1

Examining the importance of existing relationships for co-offending: a temporal network analysis in Bogotá, Colombia (2005–2018) 考察现有关系对共同犯罪的重要性:哥伦比亚波哥大<e:1>(2005-2018)的时间网络分析

IF 2.2

Applied Network Science Pub Date : 2023-01-13 DOI: 10.1007/s41109-023-00531-0

Alberto Nieto, Toby P Davies, H. Borrion

引用次数: 0

Convergence properties of optimal transport-based temporal hypergraphs 基于最优传输的时间超图的收敛性

IF 2.2

Applied Network Science Pub Date : 2023-01-11 DOI: 10.1007/s41109-022-00529-0

Diego Baptista, C. D. Bacco

引用次数: 0

Centrality-based lane interventions in road networks for improved level of service: the case of downtown Boise, Idaho 以提高服务水平为目的的道路网络中基于中心的车道干预:爱达荷州博伊西市中心的案例

IF 2.2

Applied Network Science Pub Date : 2023-01-09 DOI: 10.1007/s41109-023-00532-z

Md Ashraf Ahmed, H. M. I. Kays, A. M. Sadri

引用次数: 1

A combined synchronization index for evaluating collective action social media. 一种评价集体行动社交媒体的联合同步指标。

IF 2.2

Applied Network Science Pub Date : 2023-01-01 DOI: 10.1007/s41109-022-00526-3

Lynnette Hui Xian Ng, Kathleen M Carley

{"title":"A combined synchronization index for evaluating collective action social media.","authors":"Lynnette Hui Xian Ng, Kathleen M Carley","doi":"10.1007/s41109-022-00526-3","DOIUrl":"https://doi.org/10.1007/s41109-022-00526-3","url":null,"abstract":"Social media has provided a citizen voice, giving rise to grassroots collective action, where users deploy a concerted effort to disseminate online narratives and even carry out offline protests. Sometimes these collective action are aided by inorganic synchronization, which arise from bot actors. It is thus important to identify the synchronicity of emerging discourse on social media and the indications of organic/inorganic activity within the conversations. This provides a way of profiling an event for possibility of offline protests and violence. In this study, we build on past definitions of synchronous activity on social media- simultaneous user action-and develop a Combined Synchronization Index (CSI) which adopts a hierarchical approach in measuring user synchronicity. We apply this index on six political and social activism events on Twitter and analyzed three action types: synchronicity by hashtag, URL and @mentions.The CSI provides an overall quantification of synchronization across all action types within an event, which allows ranking of a spectrum of synchronicity across the six events. Human users have higher synchronous scores than bot users in most events; and bots and humans exhibits the most synchronized activities across all events as compared to other pairs (i.e., bot-bot and human-human). We further rely on the harmony and dissonance of CSI-Network scores with network centrality metrics to observe the presence of organic/inorganic synchronization. We hope this work aids in investigating synchronized action within social media in a collective manner.","PeriodicalId":37010,"journal":{"name":"Applied Network Science","volume":"8 1","pages":"1"},"PeriodicalIF":2.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9809510/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10509545","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: 3

Predicting variable-length paths in networked systems using multi-order generative models. 使用多阶生成模型预测网络系统中的可变长度路径。

IF 2.2

Applied Network Science Pub Date : 2023-01-01 Epub Date: 2023-09-22 DOI: 10.1007/s41109-023-00596-x

Christoph Gote, Giona Casiraghi, Frank Schweitzer, Ingo Scholtes

引用次数: 3

Overcoming vaccine hesitancy by multiplex social network targeting: an analysis of targeting algorithms and implications. 通过多重社交网络靶向克服疫苗犹豫：靶向算法和影响分析。

IF 2.2

Applied Network Science Pub Date : 2023-01-01 Epub Date: 2023-09-21 DOI: 10.1007/s41109-023-00595-y

Marzena Fügenschuh, Feng Fu

{"title":"Overcoming vaccine hesitancy by multiplex social network targeting: an analysis of targeting algorithms and implications.","authors":"Marzena Fügenschuh, Feng Fu","doi":"10.1007/s41109-023-00595-y","DOIUrl":"10.1007/s41109-023-00595-y","url":null,"abstract":"Incorporating social factors into disease prevention and control efforts is an important undertaking of behavioral epidemiology. The interplay between disease transmission and human health behaviors, such as vaccine uptake, results in complex dynamics of biological and social contagions. Maximizing intervention adoptions via network-based targeting algorithms by harnessing the power of social contagion for behavior and attitude changes largely remains a challenge. Here we address this issue by considering a multiplex network setting. Individuals are situated on two layers of networks: the disease transmission network layer and the peer influence network layer. The disease spreads through direct close contacts while vaccine views and uptake behaviors spread interpersonally within a potentially virtual network. The results of our comprehensive simulations show that network-based targeting with pro-vaccine supporters as initial seeds significantly influences vaccine adoption rates and reduces the extent of an epidemic outbreak. Network targeting interventions are much more effective by selecting individuals with a central position in the opinion network as compared to those grouped in a community or connected professionally. Our findings provide insight into network-based interventions to increase vaccine confidence and demand during an ongoing epidemic.","PeriodicalId":37010,"journal":{"name":"Applied Network Science","volume":"8 1","pages":"67"},"PeriodicalIF":2.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10514145/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41151470","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