通过社区规模和相互联系衡量在线平台的集中化程度

Q1 Social Sciences Online Social Networks and Media Pub Date : 2024-10-25 DOI:10.1016/j.osnem.2024.100292
Milo Z. Trujillo, Laurent Hébert-Dufresne, James Bagrow
{"title":"通过社区规模和相互联系衡量在线平台的集中化程度","authors":"Milo Z. Trujillo,&nbsp;Laurent Hébert-Dufresne,&nbsp;James Bagrow","doi":"10.1016/j.osnem.2024.100292","DOIUrl":null,"url":null,"abstract":"<div><div>Decentralization of online social platforms offers a variety of potential benefits, including divesting of moderator and administrator authority among a wider population, allowing a variety of communities with differing social standards to coexist, and making the platform more resilient to technical or social attack. However, a platform offering a decentralized architecture does not guarantee that users will use it in a decentralized way, and measuring the centralization of socio-technical networks is not an easy task. In this paper we introduce a method of characterizing inter-community influence, to measure the impact that removing a community would have on the remainder of a platform. Our approach provides a careful definition of “centralization” appropriate in bipartite user-community socio-technical networks, and demonstrates the inadequacy of more trivial methods for interrogating centralization such as examining the distribution of community sizes. We use this method to compare the structure of five socio-technical platforms, and find that even decentralized platforms like Mastodon are far more centralized than any synthetic networks used for comparison. We discuss how this method can be used to identify when a platform is more centralized than it initially appears, either through inherent social pressure like assortative preferential attachment, or through astroturfing by platform administrators, and how this knowledge can inform platform governance and user trust.</div></div>","PeriodicalId":52228,"journal":{"name":"Online Social Networks and Media","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Measuring centralization of online platforms through size and interconnection of communities\",\"authors\":\"Milo Z. Trujillo,&nbsp;Laurent Hébert-Dufresne,&nbsp;James Bagrow\",\"doi\":\"10.1016/j.osnem.2024.100292\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Decentralization of online social platforms offers a variety of potential benefits, including divesting of moderator and administrator authority among a wider population, allowing a variety of communities with differing social standards to coexist, and making the platform more resilient to technical or social attack. However, a platform offering a decentralized architecture does not guarantee that users will use it in a decentralized way, and measuring the centralization of socio-technical networks is not an easy task. In this paper we introduce a method of characterizing inter-community influence, to measure the impact that removing a community would have on the remainder of a platform. Our approach provides a careful definition of “centralization” appropriate in bipartite user-community socio-technical networks, and demonstrates the inadequacy of more trivial methods for interrogating centralization such as examining the distribution of community sizes. We use this method to compare the structure of five socio-technical platforms, and find that even decentralized platforms like Mastodon are far more centralized than any synthetic networks used for comparison. We discuss how this method can be used to identify when a platform is more centralized than it initially appears, either through inherent social pressure like assortative preferential attachment, or through astroturfing by platform administrators, and how this knowledge can inform platform governance and user trust.</div></div>\",\"PeriodicalId\":52228,\"journal\":{\"name\":\"Online Social Networks and Media\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-10-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Online Social Networks and Media\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S246869642400017X\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Social Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Online Social Networks and Media","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S246869642400017X","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Social Sciences","Score":null,"Total":0}
引用次数: 0

摘要

网络社交平台的去中心化提供了各种潜在的好处,包括在更广泛的人群中剥离版主和管理员的权力,允许具有不同社会标准的各种社区共存,以及使平台更能抵御技术或社会攻击。然而,提供去中心化架构的平台并不能保证用户会以去中心化的方式使用该平台,而且衡量社会技术网络的中心化程度并非易事。在本文中,我们介绍了一种描述社区间影响力的方法,以衡量移除一个社区对平台其余部分的影响。我们的方法为 "中心化 "提供了一个适合二方用户--社区社会--技术网络的细致定义,并证明了诸如检查社区规模分布等更琐碎的中心化分析方法的不足之处。我们用这种方法比较了五个社会技术平台的结构,发现即使是像 Mastodon 这样的去中心化平台,其中心化程度也远远高于用于比较的任何合成网络。我们讨论了如何利用这种方法来识别一个平台的中心化程度是否高于其最初的表面现象,这可能是由于固有的社会压力(如同类偏好依附),也可能是由于平台管理员的天马行空,以及这种知识如何为平台治理和用户信任提供信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

摘要图片

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
Measuring centralization of online platforms through size and interconnection of communities
Decentralization of online social platforms offers a variety of potential benefits, including divesting of moderator and administrator authority among a wider population, allowing a variety of communities with differing social standards to coexist, and making the platform more resilient to technical or social attack. However, a platform offering a decentralized architecture does not guarantee that users will use it in a decentralized way, and measuring the centralization of socio-technical networks is not an easy task. In this paper we introduce a method of characterizing inter-community influence, to measure the impact that removing a community would have on the remainder of a platform. Our approach provides a careful definition of “centralization” appropriate in bipartite user-community socio-technical networks, and demonstrates the inadequacy of more trivial methods for interrogating centralization such as examining the distribution of community sizes. We use this method to compare the structure of five socio-technical platforms, and find that even decentralized platforms like Mastodon are far more centralized than any synthetic networks used for comparison. We discuss how this method can be used to identify when a platform is more centralized than it initially appears, either through inherent social pressure like assortative preferential attachment, or through astroturfing by platform administrators, and how this knowledge can inform platform governance and user trust.
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
Online Social Networks and Media
Online Social Networks and Media Social Sciences-Communication
CiteScore
10.60
自引率
0.00%
发文量
32
审稿时长
44 days
期刊最新文献
How does user-generated content on Social Media affect stock predictions? A case study on GameStop Measuring centralization of online platforms through size and interconnection of communities Crowdsourcing the Mitigation of disinformation and misinformation: The case of spontaneous community-based moderation on Reddit GASCOM: Graph-based Attentive Semantic Context Modeling for Online Conversation Understanding The influence of coordinated behavior on toxicity
×
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