意大利和英国的Twitter情绪的日常模式与意大利和英国的Twitter情绪相关
Sheng Wang1, Stafford Lightman2, Nello Cristianini3
1School of Computer Science, University of Bristol, Bristol, United Kingdom.
Frontiers in psychology
|February 5, 2024
概括
推特上的情绪指标显示出日常模式,可能是由于昼夜节律. 这项研究使用了来自意大利和英国的2020年封锁数据来支持这一昼夜联系,尽量减少文化混.
科学领域:
- 计算社会科学 计算社会科学
- 时间生物学 时间生物学
- 数字化表型化是指数字化表型化.
背景情况:
- 在社交媒体数据中观察到情绪指标的日间变化.
- 之前的研究面临着混因素,阻碍了对昼夜影响的确认.
- 推特数据为情绪表达提供了大规模的实时窗口.
研究的目的:
- 为了研究Twitter内容中昼间情绪变化的昼夜性质.
- 通过在同步的国家封锁期间分析数据来最大限度地减少社会文化因素的混.
- 建立支持观察到的情绪模式的昼夜起源的相关性.
主要方法:
- 在2020年国家封锁期间,从9个意大利和54个英国城市收集了每小时的Twitter数据.
- 在这个受控数据集中分析了情绪指标的日间变化.
- 城市和国家的相关情绪指标,以识别同步的模式.
主要成果:
- 在不同城市和国家的Twitter内容中的情绪指标之间发现了显著的相关性.
- 这些相关性支持对日常情绪表达模式的昼夜影响.
- 封锁设置减少了电视和饮食习惯等常见时代因素的影响.
结论:
- 这些发现提供了强有力的证据,证明社交媒体中日间情绪变化的昼夜起源.
- 虽然支持昼夜节律,但不能完全排除影响两国共享时钟的可能性.
- 这项研究强调了数字数据在理解人类行为中的生物节奏方面的潜力.
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