Vancouver School of Economics, University of British Columbia, Vancouver, British Columbia, Canada.
Media Lab, Massachusetts Institute of Technology, Cambridge, MA, United States of America.
PLoS One. 2018 Apr 25;13(4):e0195750. doi: 10.1371/journal.pone.0195750. eCollection 2018.
We conduct the largest ever investigation into the relationship between meteorological conditions and the sentiment of human expressions. To do this, we employ over three and a half billion social media posts from tens of millions of individuals from both Facebook and Twitter between 2009 and 2016. We find that cold temperatures, hot temperatures, precipitation, narrower daily temperature ranges, humidity, and cloud cover are all associated with worsened expressions of sentiment, even when excluding weather-related posts. We compare the magnitude of our estimates with the effect sizes associated with notable historical events occurring within our data.
我们对气象条件与人类表情情绪之间的关系进行了迄今为止最大规模的调查。为此,我们使用了来自 Facebook 和 Twitter 的数千万用户在 2009 年至 2016 年期间发布的超过 35 亿条社交媒体帖子。我们发现,即使排除与天气相关的帖子,寒冷的温度、炎热的温度、降水、较窄的日温差、湿度和云层覆盖都与情绪表达的恶化有关。我们将我们的估计值与与我们数据中发生的重大历史事件相关的效应大小进行了比较。