• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

政治精英在社交媒体上分享低质量新闻来源。

Social media sharing of low-quality news sources by political elites.

作者信息

Lasser Jana, Aroyehun Segun Taofeek, Simchon Almog, Carrella Fabio, Garcia David, Lewandowsky Stephan

机构信息

Institute for Interactive Systems and Data Science, Graz University of Technology, Inffeldgasse 16C, 8010 Graz, Austria.

Complexity Science Hub Vienna, Josefstädterstraße 39, 1080 Vienna, Austria.

出版信息

PNAS Nexus. 2022 Sep 22;1(4):pgac186. doi: 10.1093/pnasnexus/pgac186.

DOI:10.1093/pnasnexus/pgac186
PMID:36380855
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7613815/
Abstract

Increased sharing of untrustworthy information on social media platforms is one of the main challenges of our modern information society. Because information disseminated by political elites is known to shape citizen and media discourse, it is particularly important to examine the quality of information shared by politicians. Here, we show that from 2016 onward, members of the Republican Party in the US Congress have been increasingly sharing links to untrustworthy sources. The proportion of untrustworthy information posted by Republicans versus Democrats is diverging at an accelerating rate, and this divergence has worsened since President Biden was elected. This divergence between parties seems to be unique to the United States as it cannot be observed in other western democracies such as Germany and the United Kingdom, where left-right disparities are smaller and have remained largely constant.

摘要

社交媒体平台上不可信信息的分享增加是我们现代信息社会的主要挑战之一。由于政治精英传播的信息已知会塑造公民和媒体话语,因此审视政治家分享的信息质量尤为重要。在此,我们表明自2016年起,美国国会中的共和党成员越来越多地分享指向不可信来源的链接。共和党人与民主党人发布的不可信信息比例正以加速的速度分化,自拜登总统当选以来,这种分化加剧。政党之间的这种分化似乎是美国独有的,因为在德国和英国等其他西方民主国家并未观察到这种情况,在这些国家,左右翼差异较小且基本保持不变。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ee5/9802276/8f830e3fbb5a/pgac186fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ee5/9802276/8f830e3fbb5a/pgac186fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ee5/9802276/8f830e3fbb5a/pgac186fig1.jpg

相似文献

1
Social media sharing of low-quality news sources by political elites.政治精英在社交媒体上分享低质量新闻来源。
PNAS Nexus. 2022 Sep 22;1(4):pgac186. doi: 10.1093/pnasnexus/pgac186.
2
Moral-Language Use by U.S. Political Elites.美国政治精英的道德语言使用
Psychol Sci. 2021 Jan;32(1):14-26. doi: 10.1177/0956797620960397. Epub 2020 Dec 11.
3
An ideological asymmetry in the diffusion of moralized content on social media among political leaders.社交媒体上政治领袖传播道德化内容的思想不对称。
J Exp Psychol Gen. 2019 Oct;148(10):1802-1813. doi: 10.1037/xge0000532. Epub 2018 Dec 27.
4
Character deprecation in fake news: Is it in supply or demand?假新闻中的人物贬低:是供应问题还是需求问题?
Group Process Intergroup Relat. 2021 Jun;24(4):624-637. doi: 10.1177/1368430220965709. Epub 2021 May 31.
5
Constituents' Inferences of Local Governments' Goals and the Relationship Between Political Party and Belief in COVID-19 Misinformation: Cross-sectional Survey of Twitter Followers of State Public Health Departments.地方政府目标的选民推断以及政党与新冠疫情错误信息中的信念之间的关系:对州公共卫生部门推特关注者的横断面调查
JMIR Infodemiology. 2022 Feb 10;2(1):e29246. doi: 10.2196/29246. eCollection 2022 Jan-Jun.
6
Elite party cues increase vaccination intentions among Republicans.精英党派暗示增加共和党人的疫苗接种意愿。
Proc Natl Acad Sci U S A. 2021 Aug 10;118(32). doi: 10.1073/pnas.2106559118.
7
Characterizing partisan political narrative frameworks about COVID-19 on Twitter.描绘推特上关于新冠疫情的党派政治叙事框架。
EPJ Data Sci. 2021;10(1):53. doi: 10.1140/epjds/s13688-021-00308-4. Epub 2021 Oct 30.
8
From alternative conceptions of honesty to alternative facts in communications by US politicians.从对诚实的另类理解到美国政客在沟通中使用的另类事实。
Nat Hum Behav. 2023 Dec;7(12):2140-2151. doi: 10.1038/s41562-023-01691-w. Epub 2023 Sep 25.
9
Who polarizes Twitter? Ideological polarization, partisan groups and strategic networked campaigning on Twitter during the 2017 and 2021 German Federal elections 'Bundestagswahlen'.谁在使推特两极分化?2017年和2021年德国联邦议院选举期间推特上的意识形态两极分化、党派团体与策略性网络竞选活动
Soc Netw Anal Min. 2022;12(1):151. doi: 10.1007/s13278-022-00958-w. Epub 2022 Oct 11.
10
Most users do not follow political elites on Twitter; those who do show overwhelming preferences for ideological congruity.大多数用户在推特上并不关注政治精英;那些关注政治精英的用户表现出对意识形态一致性的压倒性偏好。
Sci Adv. 2022 Sep 30;8(39):eabn9418. doi: 10.1126/sciadv.abn9418.

引用本文的文献

1
How media competition fuels the spread of misinformation.媒体竞争如何助长错误信息的传播。
Sci Adv. 2025 Jun 20;11(25):eadu7743. doi: 10.1126/sciadv.adu7743. Epub 2025 Jun 18.
2
Shared disbelief and shared belief: Belief and disbelief as drivers of interpersonal neural synchronization during narrative processing.共同的怀疑与共同的信念:叙事加工过程中,信念与怀疑作为人际神经同步的驱动因素
Proc Natl Acad Sci U S A. 2025 Jun 10;122(23):e2422396122. doi: 10.1073/pnas.2422396122. Epub 2025 Jun 5.
3
Different honesty conceptions align across US politicians' tweets and public replies.

本文引用的文献

1
Measuring exposure to misinformation from political elites on Twitter.测量在 Twitter 上接触到的来自政治精英的错误信息。
Nat Commun. 2022 Nov 21;13(1):7144. doi: 10.1038/s41467-022-34769-6.
2
Political audience diversity and news reliability in algorithmic ranking.算法排名中的政治受众多样性与新闻可靠性
Nat Hum Behav. 2022 Apr;6(4):495-505. doi: 10.1038/s41562-021-01276-5. Epub 2022 Feb 3.
3
Algorithmic amplification of politics on Twitter.推特上的政治算法放大。
美国政客的推文和公开回复中存在不同的诚实观念。
Nat Commun. 2025 Feb 6;16(1):1409. doi: 10.1038/s41467-025-56753-6.
4
Fact-checks focus on famous politicians, not partisans.事实核查聚焦于著名政治家,而非党派人士。
PNAS Nexus. 2024 Dec 19;4(1):pgae567. doi: 10.1093/pnasnexus/pgae567. eCollection 2025 Jan.
5
Continued influence of false accusations in forming impressions of political candidates.不实指控在形成对政治候选人的印象方面的持续影响。
PNAS Nexus. 2024 Nov 1;3(11):pgae490. doi: 10.1093/pnasnexus/pgae490. eCollection 2024 Nov.
6
Patterns of partisan toxicity and engagement reveal the common structure of online political communication across countries.党派毒性和参与模式揭示了跨国在线政治交流的共同结构。
Nat Commun. 2024 Nov 14;15(1):9560. doi: 10.1038/s41467-024-53868-0.
7
Differences in misinformation sharing can lead to politically asymmetric sanctions.信息错误传播的差异可能导致政治上的非对称制裁。
Nature. 2024 Oct;634(8034):609-616. doi: 10.1038/s41586-024-07942-8. Epub 2024 Oct 2.
8
Misunderstanding the harms of online misinformation.误解网络错误信息的危害。
Nature. 2024 Jun;630(8015):45-53. doi: 10.1038/s41586-024-07417-w. Epub 2024 Jun 5.
9
Blocking of counter-partisan accounts drives political assortment on Twitter.屏蔽对立党派账户推动了推特上的政治分类。
PNAS Nexus. 2024 Apr 15;3(5):pgae161. doi: 10.1093/pnasnexus/pgae161. eCollection 2024 May.
10
Misinformation and harmful language are interconnected, rather than distinct, challenges.错误信息和有害语言是相互关联的挑战,而非截然不同的挑战。
PNAS Nexus. 2024 Mar 12;3(3):pgae111. doi: 10.1093/pnasnexus/pgae111. eCollection 2024 Mar.
Proc Natl Acad Sci U S A. 2022 Jan 4;119(1). doi: 10.1073/pnas.2025334119.
4
Out-group animosity drives engagement on social media.外群体敌意推动社交媒体参与度。
Proc Natl Acad Sci U S A. 2021 Jun 29;118(26). doi: 10.1073/pnas.2024292118.
5
Shifting attention to accuracy can reduce misinformation online.将注意力转移到准确性上可以减少网络上的错误信息。
Nature. 2021 Apr;592(7855):590-595. doi: 10.1038/s41586-021-03344-2. Epub 2021 Mar 17.
6
Using the president's tweets to understand political diversion in the age of social media.利用总统的推文了解社交媒体时代的政治转移。
Nat Commun. 2020 Nov 10;11(1):5764. doi: 10.1038/s41467-020-19644-6.
7
Exposure to untrustworthy websites in the 2016 US election.2016 年美国大选中的不可信网站曝光。
Nat Hum Behav. 2020 May;4(5):472-480. doi: 10.1038/s41562-020-0833-x. Epub 2020 Mar 2.
8
Fake news on Twitter during the 2016 U.S. presidential election.2016年美国总统大选期间推特上的假新闻。
Science. 2019 Jan 25;363(6425):374-378. doi: 10.1126/science.aau2706.
9
Less than you think: Prevalence and predictors of fake news dissemination on Facebook.远低于你的想象:脸书上虚假新闻传播的流行程度和预测因素。
Sci Adv. 2019 Jan 9;5(1):eaau4586. doi: 10.1126/sciadv.aau4586. eCollection 2019 Jan.