CCPortal
DOI10.1073/pnas.2102147118
Polarized information ecosystems can reorganize social networks via information cascades
Tokita C.K.; Guess A.M.; Tarnita C.E.
发表日期2021
ISSN0027-8424
卷号118期号:50
英文摘要The precise mechanisms by which the information ecosystem polarizes society remain elusive. Focusing on political sorting in networks, we develop a computational model that examines how social network structure changes when individuals participate in information cascades, evaluate their behavior, and potentially rewire their connections to others as a result. Individuals follow proattitudinal information sources but are more likely to first hear and react to news shared by their social ties and only later evaluate these reactions by direct reference to the coverage of their preferred source. Reactions to news spread through the network via a complex contagion. Following a cascade, individuals who determine that their participation was driven by a subjectively “unimportant” story adjust their social ties to avoid being misled in the future. In our model, this dynamic leads social networks to politically sort when news outlets differentially report on the same topic, even when individuals do not know others’ political identities. Observational follow network data collected on Twitter support this prediction: We find that individuals in more polarized information ecosystems lose cross-ideology social ties at a rate that is higher than predicted by chance. Importantly, our model reveals that these emergent polarized networks are less efficient at diffusing information: Individuals avoid what they believe to be “unimportant” news at the expense of missing out on subjectively “important” news far more frequently. This suggests that “echo chambers”—to the extent that they exist—may not echo so much as silence. © 2021 National Academy of Sciences. All rights reserved.
英文关键词Echo chambers; News media; Political polarization; Social contagion; Social media
语种英语
scopus关键词adult; article; computer model; ecosystem; human; ideology; polarization; political identity; prediction; social media
来源期刊Proceedings of the National Academy of Sciences of the United States of America
文献类型期刊论文
条目标识符http://gcip.llas.ac.cn/handle/2XKMVOVA/250939
作者单位Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, United States; Department of Politics, Princeton University, Princeton, NJ 08544, United States; School of Public and International Affairs, Princeton University, Princeton, NJ 08544, United States
推荐引用方式
GB/T 7714
Tokita C.K.,Guess A.M.,Tarnita C.E.. Polarized information ecosystems can reorganize social networks via information cascades[J],2021,118(50).
APA Tokita C.K.,Guess A.M.,&Tarnita C.E..(2021).Polarized information ecosystems can reorganize social networks via information cascades.Proceedings of the National Academy of Sciences of the United States of America,118(50).
MLA Tokita C.K.,et al."Polarized information ecosystems can reorganize social networks via information cascades".Proceedings of the National Academy of Sciences of the United States of America 118.50(2021).
条目包含的文件
条目无相关文件。
个性服务
推荐该条目
保存到收藏夹
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Tokita C.K.]的文章
[Guess A.M.]的文章
[Tarnita C.E.]的文章
百度学术
百度学术中相似的文章
[Tokita C.K.]的文章
[Guess A.M.]的文章
[Tarnita C.E.]的文章
必应学术
必应学术中相似的文章
[Tokita C.K.]的文章
[Guess A.M.]的文章
[Tarnita C.E.]的文章
相关权益政策
暂无数据
收藏/分享

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。