在Twitter上长期COVID的脉:社交网络分析
Ikhwan Yuda Kusuma1,2, Suherman Suherman3,4
1Institute of Clinical Pharmacy, University of Szeged, H-6725 Szeged, Hungary.
Archives of Iranian medicine
|March 3, 2024
概括
对推特数据的社交网络分析揭示了讨论长期COVID的关键主题和有影响力的用户. 大多数关于长期COVID的在线对话表达了负面情绪,突出了关键信息评估的必要性.
科学领域:
- 公共卫生 公共卫生
- 社交媒体分析 社交媒体分析
- 卫生沟通健康沟通
背景情况:
- 长期COVID在急性感染后呈现复杂,持久的症状.
- 社交网络分析 (SNA) 提供了对社区健康讨论的快速洞察.
- 了解在线话语对于公共卫生干预至关重要.
研究的目的:
- 识别关于长期COVID的Twitter话语中的关键主题.
- 确定有影响力的用户和信息来源.
- 分析关于长期COVID的整体公众情绪.
主要方法:
- 采集了使用"长期COVID"关键词 (2022年12月 - 2023年2月) 的119,185条推文.
- 使用NodeXL Pro进行数据收集,使用Gephi进行网络可视化.
- 使用Azure机器学习进行情绪分析.
主要成果:
- 确定医疗专业人员,研究人员和媒体作为关键影响者.
- 标签#longCOVID是最常见的,这表明了社区的重大关注.
- 情绪分析显示,关于长期COVID的推文主要是负面的.
结论:
- 强调对来自影响者和各种来源的信息进行批判性评估.
- 强调社交媒体分析对于理解公共卫生话语的价值.
- 建议未来研究社交媒体在塑造健康观念和行为中的作用.
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