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负面情绪,睡眠障碍和温度的模式:来自微博的大数据的证据

Xiaowen Li^1,2, Jun Zhang², Bing Li³

¹College of Geography and Tourism, Anhui Normal University, Wuhu, 241000, China.

|November 29, 2023

概括

极端温度显著影响微博负面情绪 (MNE) 和睡眠障碍,明显的空气温度是关键预测因素. 女性更容易受到这些影响,这突显了气候,心理健康和行为之间的联系.

科学领域:

环境心理学环境心理学
公共卫生公共卫生
计算社会科学计算社会科学

背景情况:

以前的研究将温度与精神疾病和睡眠障碍联系起来.
温度,微博负面情绪 (MNE) 和睡眠障碍之间的关系仍未得到充分研究.
这项研究研究了气候-心理学-行为模式.

研究的目的:

为了阐明与MNE和睡眠障碍相关的温度模式.
检查MNE对睡眠障碍的预测能力.
分析性别在这些关系中的调节作用.

主要方法:

开发了一个负二项式回归模型 (NBR).
数据包括温度,表面空气温度 (AAT),微博MNE和睡眠障碍记录.
统计分析探讨了非线性关联和预测效应.

主要成果:

温度和AAT都显示了与MNE和睡眠障碍的非线性关联.
极端温度 (高和低) 有实质性的影响,而温和的温度有适度的影响.
AAT是一个比实际温度更强的预测指标,MNE有效预测睡眠障碍.

结论:

社交媒体数据可以增强心理和公共卫生问题的识别和预防.
了解温度对MNE和睡眠障碍的影响对于公共卫生战略至关重要.
性别调节了与温度相关的MNE和睡眠障碍风险的易感性.

关键词:

表面的空气温度是空气温度.情绪识别技术情绪识别技术微博是大数据的大数据.自然语言处理的实施实施.负二项式回归建模的负二项式回归建模

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