质量方法在研究推特数据中的作用 关于大众科学文章的沟通方式
Travis Noakes1, Corrie Susanna Uys2, Patricia Ann Harpur3
1Faculty of Health and Wellness Sciences, Cape Peninsula University of Technology, Cape Town, South Africa.
Frontiers in research metrics and analytics
|January 22, 2025
概括
对微博数据的定性分析为科学传播提供了深入的见解,揭示了专业人士如何在辩论中使用文章并为更广泛的覆盖范围调整内容. 这种方法增强了超越大数据模式的理解.
科学领域:
- 科学传播科学传播
- 卫生沟通健康沟通
- 社交媒体研究 社交媒体研究
背景情况:
- 大数据研究往往忽视了在线科学对话的定性细微差别.
- 在理解如何将定性方法应用于关于科学文章微博的小数据集方面存在差距.
- 虽然社交媒体有助于文章传播,但对微博实践的定性研究有限.
研究的目的:
- 探索定性分析如何丰富科学传播研究,专注于微博.
- 展示整合定性分析与大数据方法的价值,以更深入地理解互动.
- 为了分析推广和讨论一个流行的,非正统的科学文章在Twitter上的两年.
主要方法:
- 混合方法方法结合了对一个小数据集的定性和定量分析.
- 一个实用主义者使用NVivoTM进行多模式内容分析.
- 由统计学家使用MAXQDATM进行语义网络分析和元推理.
主要成果:
- 卫生专业人士分享了这篇文章,将其受欢迎程度与其在健康科学辩论中的作用联系起来.
- 这篇文章被异议专业人士用来支持新的范式,并为更广泛的受众进行本地化 (翻译).
- 语义分析证实了推特内容和文章主题之间的一致性,表明了亲社会讨论.
结论:
- 对微博数据的定性分析为科学传播中的专业身份和立场提供了有价值的背景.
- 整合定性方法与大数据增强了对在线科学文章推广和讨论的理解.
- 通过使用定性软件确定了数据准备和分析的挑战,并提出了未来研究的领域.
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