• 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

携手战胜新冠疫情:理解地方政府的社交媒体沟通

Getting through COVID-19 together: Understanding local governments' social media communication.

作者信息

Górska Anna, Dobija Dorota, Grossi Giuseppe, Staniszewska Zuzanna

机构信息

Kozminski University, Jagielonska 57, 03-301 Warsaw, Poland.

Kozmniski University, Poland.

出版信息

Cities. 2022 Feb;121:103453. doi: 10.1016/j.cities.2021.103453. Epub 2021 Sep 16.

DOI:10.1016/j.cities.2021.103453
PMID:34566232
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8448384/
Abstract

This study provides new insights into how local governments (LGs) manage pandemic-related crisis communication with citizens on their social media (SM) profiles. We analyze over 3000 posts published on SM profiles of selected LGs in Poland to get insights on rhetorical communication strategies during the COVID-19 pandemic. We document LGs as they go beyond the simple transmission of information to citizens and use SM in an engaging and educational manner. We found three types of rhetorical strategies and their resonance with the public. Our analysis suggests that LGs are likely to apply the Together communication strategy, which is the most engaging.

摘要

本研究为地方政府如何在其社交媒体(SM)页面上与公民进行与疫情相关的危机沟通提供了新的见解。我们分析了波兰选定地方政府在SM页面上发布的3000多篇帖子,以了解新冠疫情期间的修辞沟通策略。我们记录了地方政府如何超越向公民简单传递信息的范畴,以引人入胜且具有教育意义的方式使用社交媒体。我们发现了三种修辞策略及其与公众的共鸣。我们的分析表明,地方政府可能会采用最具吸引力的“团结”沟通策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7df5/8448384/a1de27987625/gr2_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7df5/8448384/064e4a136995/gr1_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7df5/8448384/a1de27987625/gr2_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7df5/8448384/064e4a136995/gr1_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7df5/8448384/a1de27987625/gr2_lrg.jpg

相似文献

1
Getting through COVID-19 together: Understanding local governments' social media communication.携手战胜新冠疫情:理解地方政府的社交媒体沟通
Cities. 2022 Feb;121:103453. doi: 10.1016/j.cities.2021.103453. Epub 2021 Sep 16.
2
Association Between Public Opinion and Malaysian Government Communication Strategies About the COVID-19 Crisis: Content Analysis of Image Repair Strategies in Social Media.公众舆论与马来西亚政府关于 COVID-19 危机沟通策略的关系:社交媒体中形象修复策略的内容分析。
J Med Internet Res. 2021 Aug 4;23(8):e28074. doi: 10.2196/28074.
3
Citizens' Adherence to COVID-19 Mitigation Recommendations by the Government: A 3-Country Comparative Evaluation Using Web-Based Cross-Sectional Survey Data.公民对政府新冠疫情缓解建议的遵守情况:基于网络横断面调查数据的三国比较评估
J Med Internet Res. 2020 Aug 11;22(8):e20634. doi: 10.2196/20634.
4
Evaluating South African and Namibian governments' use of digital media during Covid-19.评估南非和纳米比亚政府在新冠疫情期间对数字媒体的使用情况。
World Med Health Policy. 2022 Jun;14(2):325-342. doi: 10.1002/wmh3.507. Epub 2022 Mar 23.
5
Local governments' use of social media during the COVID-19 pandemic: The case of Portugal.地方政府在新冠疫情期间对社交媒体的使用:以葡萄牙为例。
Gov Inf Q. 2021 Oct;38(4):101620. doi: 10.1016/j.giq.2021.101620. Epub 2021 Aug 6.
6
Analyzing U.S. State Governments' COVID-19 Homepages during the Initial Lockdown in March and April 2020: Information Content and Interactivity.分析 2020 年 3 月和 4 月美国各州政府在新冠疫情初始封锁期间的官方主页:信息内容和交互性。
Health Commun. 2023 Jun;38(7):1327-1337. doi: 10.1080/10410236.2021.2007574. Epub 2021 Dec 1.
7
Local governments' communication through Facebook. Evidences from COVID-19 pandemic in Italy.地方政府通过脸书进行的沟通。来自意大利新冠疫情的证据。
J Public Aff. 2021 Nov;21(4):e2551. doi: 10.1002/pa.2551. Epub 2020 Nov 25.
8
Grappling With the COVID-19 Health Crisis: Content Analysis of Communication Strategies and Their Effects on Public Engagement on Social Media.应对新冠疫情健康危机:社交媒体上传播策略及其对公众参与度影响的内容分析
J Med Internet Res. 2020 Aug 24;22(8):e21360. doi: 10.2196/21360.
9
Social presence for strategic health messages: An examination of state governments' use of Twitter to tackle the Covid-19 pandemic.战略健康信息的社会存在感:对州政府利用推特应对新冠疫情的考察。
Public Relat Rev. 2022 Nov;48(4):102223. doi: 10.1016/j.pubrev.2022.102223. Epub 2022 Jun 23.
10
Emotions of COVID-19: Content Analysis of Self-Reported Information Using Artificial Intelligence.COVID-19 情绪:使用人工智能进行自我报告信息的内容分析。
J Med Internet Res. 2021 Apr 30;23(4):e27341. doi: 10.2196/27341.

引用本文的文献

1
Influence of Strategic Crisis Communication on Public Perceptions during Public Health Crises: Insights from YouTube Chinese Media.公共卫生危机期间战略危机沟通对公众认知的影响:来自YouTube中文媒体的见解
Behav Sci (Basel). 2024 Jan 26;14(2):91. doi: 10.3390/bs14020091.
2
The Role of Social Media in Health Misinformation and Disinformation During the COVID-19 Pandemic: Bibliometric Analysis.社交媒体在 COVID-19 大流行期间健康错误信息和虚假信息中的作用:文献计量分析。
JMIR Infodemiology. 2023 Sep 20;3:e48620. doi: 10.2196/48620.
3
Public Officials' Engagement on Social Media During the Rollout of the COVID-19 Vaccine: Content Analysis of Tweets.

本文引用的文献

1
Unpacking the black box: How to promote citizen engagement through government social media during the COVID-19 crisis.打开黑匣子:如何在新冠疫情危机期间通过政府社交媒体促进公民参与。
Comput Human Behav. 2020 Sep;110:106380. doi: 10.1016/j.chb.2020.106380. Epub 2020 Apr 12.
新冠疫苗推广期间公职人员在社交媒体上的参与情况:推文内容分析
JMIR Infodemiology. 2023 Jul 20;3:e41582. doi: 10.2196/41582.
4
Striving for wellbeing digitally in the city amidst the pandemic: Solidarity through Twitter in Ankara.疫情期间在城市中通过数字手段追求福祉:安卡拉通过推特展现的团结。
Habitat Int. 2023 Jul;137:102846. doi: 10.1016/j.habitatint.2023.102846. Epub 2023 May 25.
5
Information under lockdown: A content analysis of government communication strategies on Facebook during the COVID-19 outbreak.封锁下的信息:对新冠疫情期间政府在脸书上的沟通策略的内容分析
Heliyon. 2023 Apr;9(4):e15562. doi: 10.1016/j.heliyon.2023.e15562. Epub 2023 Apr 18.
6
The road to recovery: Sensing public opinion towards reopening measures with social media data in post-lockdown cities.复苏之路:利用解封后城市的社交媒体数据感知公众对重新开放措施的看法。
Cities. 2023 Jan;132:104054. doi: 10.1016/j.cities.2022.104054. Epub 2022 Nov 3.
7
Deep learning modeling of public's sentiments towards temporal evolution of COVID-19 transmission.公众对新冠病毒传播时间演变的情绪的深度学习建模
Appl Soft Comput. 2022 Dec;131:109728. doi: 10.1016/j.asoc.2022.109728. Epub 2022 Oct 20.