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在 COVID-19 大流行期间通过积极和团结的信息进行健康传播:对 Facebook 使用情况的自动化内容分析。

Health Communication through Positive and Solidarity Messages Amid the COVID-19 Pandemic: Automated Content Analysis of Facebook Uses.

机构信息

Department of Communication, Faculty of Social Sciences, University of Macau, Macao, China.

Institute of Communication and Health, Lugano University, 6900 Lugano, Switzerland.

出版信息

Int J Environ Res Public Health. 2022 May 19;19(10):6159. doi: 10.3390/ijerph19106159.

DOI:10.3390/ijerph19106159
PMID:35627696
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9141526/
Abstract

The COVID-19 outbreak has caused significant stress in our lives, which potentially increases frustration, fear, and resentful emotions. Managing stress is complex, but helps to alleviate negative psychological effects. In order to understand how the public coped with stress during the COVID-19 pandemic, we used Macao as a case study and collected 104,827 COVID-19 related posts from Facebook through data mining, from 1 January to 31 December 2020. Divominer, a big-data analysis tool supported by computational algorithm, was employed to identify themes and facilitate machine coding and analysis. A total of 60,875 positive messages were identified, with 24,790 covering positive psychological themes, such as "anti-epidemic", "solidarity", "hope", "gratitude", "optimism", and "grit". Messages that mentioned "anti-epidemic", "solidarity", and "hope" were the most prevalent, while different crisis stages, key themes and media elements had various impacts on public involvement. To the best of our knowledge, this is the first-ever study in the Chinese context that uses social media to clarify the awareness of solidarity. Positive messages are needed to empower social media users to shoulder their shared responsibility to tackle the crisis. The findings provide insights into users' needs for improving their subjective well-being to mitigate the negative psychological impact of the pandemic.

摘要

新冠疫情的爆发给我们的生活带来了巨大的压力,这可能会增加挫败感、恐惧和怨恨等情绪。应对压力是一个复杂的问题,但有助于减轻负面的心理影响。为了了解公众在新冠疫情期间如何应对压力,我们选择澳门作为案例研究,并通过数据挖掘从 2020 年 1 月 1 日至 12 月 31 日在 Facebook 上收集了 104827 条与新冠疫情相关的帖子。我们使用了 Divominer 这个由计算算法支持的大数据分析工具来识别主题,并促进机器编码和分析。共识别出 60875 条积极的信息,其中 24790 条涵盖了积极的心理主题,如“抗疫”、“团结”、“希望”、“感恩”、“乐观”和“坚韧”。提到“抗疫”、“团结”和“希望”的信息最为常见,而不同的危机阶段、关键主题和媒体元素对公众的参与有不同的影响。据我们所知,这是首次在中国语境下使用社交媒体来阐明团结意识的研究。积极的信息可以增强社交媒体用户的力量,让他们共同承担应对危机的责任。研究结果为了解用户改善主观幸福感以减轻疫情负面影响的需求提供了新的视角。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/57aa/9141526/c9bfbd32f0a6/ijerph-19-06159-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/57aa/9141526/569e3828a802/ijerph-19-06159-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/57aa/9141526/3a82124b5726/ijerph-19-06159-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/57aa/9141526/c9bfbd32f0a6/ijerph-19-06159-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/57aa/9141526/569e3828a802/ijerph-19-06159-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/57aa/9141526/3a82124b5726/ijerph-19-06159-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/57aa/9141526/c9bfbd32f0a6/ijerph-19-06159-g003.jpg

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