解构中心性:在网络中进行局部思考和全球排名

Sibel Adali, Xiaohui Lu, M. Magdon-Ismail
{"title":"解构中心性:在网络中进行局部思考和全球排名","authors":"Sibel Adali, Xiaohui Lu, M. Magdon-Ismail","doi":"10.1145/2492517.2492531","DOIUrl":null,"url":null,"abstract":"We examine whether the prominence of individuals in different social networks is determined by their position in their local network or by how the community to which they belong relates to other communities. To this end, we introduce two new measures of centrality, both based on communities in the network: local and community centrality. Community centrality is a novel concept that we introduce to describe how central one's community is within the whole network. We introduce an algorithm to estimate the distance between communities and use it to find the centrality of communities. Using data from several social networks, we show that community centrality is able to capture the importance of communities in the whole network. We then conduct a detailed study of different social networks and determine how various global measures of prominence relate to structural centrality measures.Our measures deconstruct global centrality along local and community dimensions. In some cases, prominence is determined almost exclusively by local information, while in others a mix of local and community centrality matters. Our methodology is a step toward understanding of the processes that contribute to an actor's prominence in a network.","PeriodicalId":442230,"journal":{"name":"2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2013)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Deconstructing centrality: Thinking locally and ranking globally in networks\",\"authors\":\"Sibel Adali, Xiaohui Lu, M. Magdon-Ismail\",\"doi\":\"10.1145/2492517.2492531\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We examine whether the prominence of individuals in different social networks is determined by their position in their local network or by how the community to which they belong relates to other communities. To this end, we introduce two new measures of centrality, both based on communities in the network: local and community centrality. Community centrality is a novel concept that we introduce to describe how central one's community is within the whole network. We introduce an algorithm to estimate the distance between communities and use it to find the centrality of communities. Using data from several social networks, we show that community centrality is able to capture the importance of communities in the whole network. We then conduct a detailed study of different social networks and determine how various global measures of prominence relate to structural centrality measures.Our measures deconstruct global centrality along local and community dimensions. In some cases, prominence is determined almost exclusively by local information, while in others a mix of local and community centrality matters. Our methodology is a step toward understanding of the processes that contribute to an actor's prominence in a network.\",\"PeriodicalId\":442230,\"journal\":{\"name\":\"2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2013)\",\"volume\":\"65 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-08-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2013)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2492517.2492531\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2013)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2492517.2492531","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

摘要

我们研究了个人在不同社会网络中的突出地位是由他们在当地网络中的地位决定的,还是由他们所属的社区与其他社区的关系决定的。为此,我们引入了两种新的中心性度量方法,它们都基于网络中的社区:本地中心性和社区中心性。社区中心性是我们引入的一个新概念,用来描述一个人的社区在整个网络中的中心地位。我们引入了一种算法来估计群落之间的距离,并用它来寻找群落的中心性。使用来自几个社交网络的数据,我们表明社区中心性能够捕捉社区在整个网络中的重要性。然后,我们对不同的社会网络进行了详细的研究,并确定了各种突出的全球措施与结构中心性措施之间的关系。我们的措施沿着地方和社区维度解构全球中心性。在某些情况下,突出程度几乎完全取决于当地的信息,而在另一些情况下,地方和社区的中心地位很重要。我们的方法是朝着理解导致演员在网络中突出地位的过程迈出的一步。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Deconstructing centrality: Thinking locally and ranking globally in networks
We examine whether the prominence of individuals in different social networks is determined by their position in their local network or by how the community to which they belong relates to other communities. To this end, we introduce two new measures of centrality, both based on communities in the network: local and community centrality. Community centrality is a novel concept that we introduce to describe how central one's community is within the whole network. We introduce an algorithm to estimate the distance between communities and use it to find the centrality of communities. Using data from several social networks, we show that community centrality is able to capture the importance of communities in the whole network. We then conduct a detailed study of different social networks and determine how various global measures of prominence relate to structural centrality measures.Our measures deconstruct global centrality along local and community dimensions. In some cases, prominence is determined almost exclusively by local information, while in others a mix of local and community centrality matters. Our methodology is a step toward understanding of the processes that contribute to an actor's prominence in a network.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Statistical analysis and implications of SNS search in under-developed countries Identifying unreliable sources of skill and competency information Assessing group cohesion in homophily networks Exploiting online social data in ontology learning for event tracking and emergency response Event identification for social streams using keyword-based evolving graph sequences
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1