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归因还是共情?政府社交媒体舆情回应框架研究——对21起舆情事件的定性比较分析

Attribution or empathy? A study on the public opinion response framework of government social media-a qualitative comparative analysis of 21 public opinion incidents.

作者信息

Li Yuan, Liu Mingyang

机构信息

School of Journalism and Communication, Shandong University, Jinan, China.

出版信息

Front Psychol. 2025 Jul 4;16:1556030. doi: 10.3389/fpsyg.2025.1556030. eCollection 2025.

DOI:10.3389/fpsyg.2025.1556030
PMID:40688550
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12273600/
Abstract

This study examined the influencing factors of government social media's public opinion response framework from the perspective of public opinion ecological governance, and provides an optimization strategy for its response. According to a qualitative comparative analysis (fsQCA) of 21 public opinion incidents, it was found that government social media tended to employ a context-responsibility framework when faced with the combined paths of high netizen attention and strong negative sentiment, as well as high media participation and elevated levels of government intervention. In contrast, a subject-emotional framework is preferred in scenarios with weak negative sentiment and incomplete initial media reporting, or when high media participation coincides with highly sensitive event types. According to these findings, issues of attribution inertia and post-event empathy in government social media responses were identified and the application of public opinion ecosystem governance principles were advocated to enhance dynamic balance, openness, and foresight, thereby optimizing capabilities in public opinion regulation, deep communication, and proactive "preventive care."

摘要

本研究从舆情生态治理视角审视了政府社交媒体舆情回应框架的影响因素,并为其回应提供了优化策略。通过对21起舆情事件的定性比较分析(模糊集定性比较分析)发现,政府社交媒体在面对网民关注度高、负面情绪强烈,以及媒体参与度高和政府干预程度高的组合路径时,倾向于采用情境-责任框架。相比之下,在负面情绪较弱、初始媒体报道不完整的情况下,或者当媒体参与度高与事件类型高度敏感同时出现时,更倾向于采用主体-情感框架。根据这些发现,识别出政府社交媒体回应中的归因惯性和事后同理心问题,并倡导应用舆情生态系统治理原则来增强动态平衡、开放性和前瞻性,从而优化舆情监管、深度沟通和主动“预防护理”能力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0413/12273600/17eb012e90f8/fpsyg-16-1556030-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0413/12273600/17eb012e90f8/fpsyg-16-1556030-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0413/12273600/17eb012e90f8/fpsyg-16-1556030-g001.jpg

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本文引用的文献

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Spatiotemporal pattern evolution and influencing factors of online public opinion--Evidence from the early-stage of COVID-19 in China.网络舆情的时空格局演变及影响因素——来自中国新冠肺炎疫情初期的证据
Heliyon. 2023 Sep 12;9(9):e20080. doi: 10.1016/j.heliyon.2023.e20080. eCollection 2023 Sep.
2
Citizens' trust in government as a function of good governance and government agency's provision of quality information on social media during COVID-19.公民对政府的信任是善治以及政府机构在新冠疫情期间在社交媒体上提供高质量信息的函数。
Gov Inf Q. 2021 Oct;38(4):101597. doi: 10.1016/j.giq.2021.101597. Epub 2021 Jun 23.
3
Parallel evolution and response decision method for public sentiment based on system dynamics.
基于系统动力学的舆情平行演化与响应决策方法
Eur J Oper Res. 2020 Dec 16;287(3):1131-1148. doi: 10.1016/j.ejor.2020.05.025. Epub 2020 May 23.
4
How behavioural sciences can promote truth, autonomy and democratic discourse online.行为科学如何促进网络上的真相、自主和民主话语。
Nat Hum Behav. 2020 Nov;4(11):1102-1109. doi: 10.1038/s41562-020-0889-7. Epub 2020 Jun 15.