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DOI | 10.1073/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 |
ISSN | 0027-8424 |
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). |
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