Concentration without cumulative advantage: the distribution of news source attention in online communities

IF 6.1 1区 文学 Q1 COMMUNICATION
Nick Hagar, Aaron Shaw
{"title":"Concentration without cumulative advantage: the distribution of news source attention in online communities","authors":"Nick Hagar, Aaron Shaw","doi":"10.1093/joc/jqac032","DOIUrl":null,"url":null,"abstract":"Many attention markets exhibit stable patterns of concentration, where a few producers attract and sustain a far greater share of the audience than others. This inequality often follows patterns consistent with cumulative advantage, a process in which performance compounds over time. Attention to news sources online possesses these characteristics; however, online audiences also fragment across many disparate news producers. How do social media and recommender systems contribute to these attention dynamics? In this study, we examine two paradigmatic models: concentration driven by cumulative advantage and fragmentation driven by stochasticity. We evaluate these models against a large-scale empirical dataset of news source attention in the popular social media site Reddit. While we find high levels of attention concentration, we do not find the stable popularity over time that characterizes cumulative advantage. Rather, sources gain and lose popularity seemingly at random, aligning with a stochastic model. These results demonstrate the persistence of attention inequality, even in the absence of a strong driving mechanism. They also suggest that social media systems can undermine the accumulation of attention to the most prominent news sources. Digital attention markets striving for more equitable allocation require novel mechanisms of organizing and distributing information.","PeriodicalId":48410,"journal":{"name":"Journal of Communication","volume":"46 17","pages":""},"PeriodicalIF":6.1000,"publicationDate":"2022-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Communication","FirstCategoryId":"98","ListUrlMain":"https://doi.org/10.1093/joc/jqac032","RegionNum":1,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMMUNICATION","Score":null,"Total":0}
引用次数: 3

Abstract

Many attention markets exhibit stable patterns of concentration, where a few producers attract and sustain a far greater share of the audience than others. This inequality often follows patterns consistent with cumulative advantage, a process in which performance compounds over time. Attention to news sources online possesses these characteristics; however, online audiences also fragment across many disparate news producers. How do social media and recommender systems contribute to these attention dynamics? In this study, we examine two paradigmatic models: concentration driven by cumulative advantage and fragmentation driven by stochasticity. We evaluate these models against a large-scale empirical dataset of news source attention in the popular social media site Reddit. While we find high levels of attention concentration, we do not find the stable popularity over time that characterizes cumulative advantage. Rather, sources gain and lose popularity seemingly at random, aligning with a stochastic model. These results demonstrate the persistence of attention inequality, even in the absence of a strong driving mechanism. They also suggest that social media systems can undermine the accumulation of attention to the most prominent news sources. Digital attention markets striving for more equitable allocation require novel mechanisms of organizing and distributing information.

Abstract Image

没有累积优势的集中:新闻源注意力在网络社区的分布
许多注意力市场表现出稳定的集中模式,少数制作人吸引并维持了比其他制作人更大的观众份额。这种不平等通常遵循与累积优势相一致的模式,这是一个随着时间的推移,业绩会变得更加复杂的过程。对网络新闻来源的关注具有这些特点;然而,在线观众也分散在许多不同的新闻制作人身上。社交媒体和推荐系统是如何促成这些注意力动态的?在本研究中,我们考察了两种范式模型:累积优势驱动的集中化模型和随机性驱动的碎片化模型。我们根据流行的社交媒体网站Reddit上的新闻来源关注的大规模经验数据集来评估这些模型。虽然我们发现了高度的注意力集中,但我们没有发现随着时间的推移而稳定的受欢迎程度,这是累积优势的特征。更确切地说,消息来源的受欢迎程度的增加和减少似乎是随机的,与随机模型一致。这些结果表明,即使在缺乏强有力的驱动机制的情况下,注意力不平等仍然存在。他们还表示,社交媒体系统可能会破坏对最重要新闻来源的关注积累。追求更公平分配的数字注意力市场需要新的信息组织和分发机制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Journal of Communication
Journal of Communication COMMUNICATION-
CiteScore
11.60
自引率
5.10%
发文量
41
期刊介绍: The Journal of Communication, the flagship journal of the International Communication Association, is a vital publication for communication specialists and policymakers alike. Focusing on communication research, practice, policy, and theory, it delivers the latest and most significant findings in communication studies. The journal also includes an extensive book review section and symposia of selected studies on current issues. JoC publishes top-quality scholarship on all aspects of communication, with a particular interest in research that transcends disciplinary and sub-field boundaries.
×
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