社交网络分析:游戏实验

T. Ben-Zvi
{"title":"社交网络分析:游戏实验","authors":"T. Ben-Zvi","doi":"10.1145/1807406.1807490","DOIUrl":null,"url":null,"abstract":"This study examines how early business relationships in company networks may predict later performance and centrality. We define a way of classifying centrality trajectories in social networks, providing a method that can be used more generally to predict network change over time. Employing a game simulation, we show that there are strategies that correlate with eventual centrality and profit, and other strategies that correlate with poor performance.","PeriodicalId":142982,"journal":{"name":"Behavioral and Quantitative Game Theory","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2010-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Social networks analysis: a game experiment\",\"authors\":\"T. Ben-Zvi\",\"doi\":\"10.1145/1807406.1807490\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study examines how early business relationships in company networks may predict later performance and centrality. We define a way of classifying centrality trajectories in social networks, providing a method that can be used more generally to predict network change over time. Employing a game simulation, we show that there are strategies that correlate with eventual centrality and profit, and other strategies that correlate with poor performance.\",\"PeriodicalId\":142982,\"journal\":{\"name\":\"Behavioral and Quantitative Game Theory\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-05-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Behavioral and Quantitative Game Theory\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/1807406.1807490\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Behavioral and Quantitative Game Theory","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1807406.1807490","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

本研究探讨了公司网络中的早期业务关系如何预测后来的绩效和中心性。我们定义了一种在社交网络中对中心性轨迹进行分类的方法,提供了一种可以更广泛地用于预测网络随时间变化的方法。通过游戏模拟,我们发现有些策略与最终的中心性和利润相关,而有些策略与糟糕的表现相关。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Social networks analysis: a game experiment
This study examines how early business relationships in company networks may predict later performance and centrality. We define a way of classifying centrality trajectories in social networks, providing a method that can be used more generally to predict network change over time. Employing a game simulation, we show that there are strategies that correlate with eventual centrality and profit, and other strategies that correlate with poor performance.
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
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信