探索 COVID-19 大流行对日本 Twitter 的影响:对计划被打乱及其后果的定性分析。

IF 3.5 Q1 HEALTH CARE SCIENCES & SERVICES JMIR infodemiology Pub Date : 2024-04-01 DOI:10.2196/49699
Masaru Kamba, Wan Jou She, Kiki Ferawati, Shoko Wakamiya, Eiji Aramaki
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引用次数: 0

摘要

背景:尽管 COVID-19 是一种流行病,但其传播的影响却超出了公共卫生的范围,影响到经济、教育、工作方式和社会关系等领域。记录公众意见并估计大流行后的长期潜在影响的调查研究对该领域具有重要价值:本研究旨在通过分析日本人在社交媒体上对其生活计划被打乱情况的自我披露,发现并追踪日本人在 COVID-19 大流行期间的担忧。这种方法为确定生活在日本的个人可能需要进一步关注的问题提供了替代证据:我们使用查询短语 Corona-no-sei("由于 COVID-19"、"因为 COVID-19 "或 "考虑 COVID-19")提取了 300,778 条推文,从而确定了因大流行病而中断的活动和生活计划。我们分析了推文数量与 COVID-19 案例之间的相关性,并对频繁出现的词语进行了研究:结果:提取了与 Corona no-sei 共同出现的前 20 个名词、动词和名词加动词对。前 5 个关键词是毕业典礼、取消、学校、工作和事件。前 5 个动词是消失、去、休息、可以去和结束。我们的研究结果表明,当日本政府宣布首次进入紧急状态时,教育成为最受关注的问题。我们还观察到,对卫生纸等物资短缺的焦虑突然激增。随着疫情的持续和更多紧急状态的宣布,我们注意到人们的关注点开始转向长期问题,包括职业、社会关系和教育:我们的研究结合了机器学习技术,通过使用推特数据进行疾病监测,从而在日本政府宣布紧急状态的三个阶段中识别出潜在的关注点(例如,教育和工作条件受到破坏)。与 COVID-19 病例数的比较为短期和长期的社会影响提供了宝贵的见解,强调了在制定政策和支持受流行病影响者时考虑公民观点的重要性,特别是在日本政府决策的背景下。
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Exploring the Impact of the COVID-19 Pandemic on Twitter in Japan: Qualitative Analysis of Disrupted Plans and Consequences.

Background: Despite being a pandemic, the impact of the spread of COVID-19 extends beyond public health, influencing areas such as the economy, education, work style, and social relationships. Research studies that document public opinions and estimate the long-term potential impact after the pandemic can be of value to the field.

Objective: This study aims to uncover and track concerns in Japan throughout the COVID-19 pandemic by analyzing Japanese individuals' self-disclosure of disruptions to their life plans on social media. This approach offers alternative evidence for identifying concerns that may require further attention for individuals living in Japan.

Methods: We extracted 300,778 tweets using the query phrase Corona-no-sei ("due to COVID-19," "because of COVID-19," or "considering COVID-19"), enabling us to identify the activities and life plans disrupted by the pandemic. The correlation between the number of tweets and COVID-19 cases was analyzed, along with an examination of frequently co-occurring words.

Results: The top 20 nouns, verbs, and noun plus verb pairs co-occurring with Corona no-sei were extracted. The top 5 keywords were graduation ceremony, cancel, school, work, and event. The top 5 verbs were disappear, go, rest, can go, and end. Our findings indicate that education emerged as the top concern when the Japanese government announced the first state of emergency. We also observed a sudden surge in anxiety about material shortages such as toilet paper. As the pandemic persisted and more states of emergency were declared, we noticed a shift toward long-term concerns, including careers, social relationships, and education.

Conclusions: Our study incorporated machine learning techniques for disease monitoring through the use of tweet data, allowing the identification of underlying concerns (eg, disrupted education and work conditions) throughout the 3 stages of Japanese government emergency announcements. The comparison with COVID-19 case numbers provides valuable insights into the short- and long-term societal impacts, emphasizing the importance of considering citizens' perspectives in policy-making and supporting those affected by the pandemic, particularly in the context of Japanese government decision-making.

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Association Between X/Twitter and Prescribing Behavior During the COVID-19 Pandemic: Retrospective Ecological Study. Correction: Exploring the Impact of the COVID-19 Pandemic on Twitter in Japan: Qualitative Analysis of Disrupted Plans and Consequences. The Complex Interaction Between Sleep-Related Information, Misinformation, and Sleep Health: A Call for Comprehensive Research on Sleep Infodemiology and Infoveillance. Understanding and Combating Misinformation: An Evolutionary Perspective. Detection and Characterization of Online Substance Use Discussions Among Gamers: Qualitative Retrospective Analysis of Reddit r/StopGaming Data.
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