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艰难时期的组织意义建构:非政府组织在社交媒体上关于新冠疫情问题话语社群的生态

Organizational sensemaking in tough times: The ecology of NGOs' COVID-19 issue discourse communities on social media.

作者信息

Li Yiqi, Shin Jieun, Sun Jingyi, Kim Hye Min, Qu Yan, Yang Aimei

机构信息

Annenberg School of Communication and Journalism, University of Southern California, United States.

College of Journalism and Communications, University of Florida, United States.

出版信息

Comput Human Behav. 2021 Sep;122:106838. doi: 10.1016/j.chb.2021.106838. Epub 2021 Apr 28.

DOI:10.1016/j.chb.2021.106838
PMID:34754136
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8569519/
Abstract

NGOs are important civil actors in societies' emergency and disaster responses, and they come together on social media to identify prominent issues and coordinate issue responses. This research explores how U.S. NGO form topic-driven communities on social media to discuss and build representational strategic networks around issues related to the COVID-19 pandemic. Drawing from Issue Niche Theory, we examined how NGOs' networks and discourse evolved before and after the general public paid great attention to the COVID-19 issue and how such patterns changed across the whole issue niche and sub-issue niches. We analyzed the evolution of Twitter-based networks and discourse of 2,588 NGOs in the first five months of the COVID-19 outbreak in the United States. Our analysis revealed important factors that shape tie formation patterns in the NGOs' communities in this novel issue niche. The findings show that NGOs' discourses help to orient the organizational community to identify most salient issues. Finally, changes in the discourse patterns reflected changes in the communication networks in the NGO community.

摘要

非政府组织是社会应急和灾害应对中的重要民间行为体,它们在社交媒体上聚集,以识别突出问题并协调问题应对措施。本研究探讨了美国非政府组织如何在社交媒体上形成以话题为驱动的社区,围绕与新冠疫情相关的问题讨论并构建代表性战略网络。借鉴议题利基理论,我们研究了在公众高度关注新冠疫情问题之前和之后,非政府组织的网络和话语是如何演变的,以及这种模式在整个议题利基和子议题利基中是如何变化的。我们分析了美国新冠疫情爆发头五个月里,2588个非政府组织基于推特的网络和话语的演变。我们的分析揭示了在这个新的议题利基中,塑造非政府组织社区中联系形成模式的重要因素。研究结果表明,非政府组织的话语有助于引导组织社区识别最突出的问题。最后,话语模式的变化反映了非政府组织社区中通信网络的变化。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9dc5/8569519/c00153615728/gr6a_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9dc5/8569519/8d53dfa5d7a5/gr1_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9dc5/8569519/b15e9a5cbe41/gr2_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9dc5/8569519/1ff4e48fb3cb/gr3_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9dc5/8569519/3fc8970ec5cb/gr4_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9dc5/8569519/a14b74e895f7/gr5_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9dc5/8569519/c00153615728/gr6a_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9dc5/8569519/8d53dfa5d7a5/gr1_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9dc5/8569519/b15e9a5cbe41/gr2_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9dc5/8569519/1ff4e48fb3cb/gr3_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9dc5/8569519/3fc8970ec5cb/gr4_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9dc5/8569519/a14b74e895f7/gr5_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9dc5/8569519/c00153615728/gr6a_lrg.jpg

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