幸福的地理：连接Twitter的情绪和表达，人口统计学和客观的地方特征
The Geography of Happiness: Connecting Twitter sentiment and expression, demographics, and objective characteristics of place
摘要：
我们对美国各地的个人实时表达与广泛的情感，地理，人口统计和健康特征之间的相关性进行了详细的调查。我们这样做是通过结合（1）一个巨大的，地理标记的数据集，包括超过8000万字，在最近几年的过程中产生的社交网络服务Twitter和（2）每年调查的所有50个州和近400个城市人口的特征。在众多结果中，我们根据州和城市在词汇使用方面的相似性生成了州和城市的分类;估计州和城市的幸福水平;将高度解析的人口统计特征与幸福水平相关联;并将词汇选择和信息长度与城市特征（如教育水平和肥胖率）联系起来。我们的研究结果表明，社交媒体可能被用来估计实时水平和人口水平指标的变化，如肥胖率。
英文摘要：
We conduct a detailed investigation of correlations between real-time expressions of individuals made across the United States and a wide range of emotional, geographic, demographic, and health characteristics. We do so by combining (1) a massive, geo-tagged data set comprising over 80 million words generated over the course of several recent years on the social network service Twitter and (2) annually-surveyed characteristics of all 50 states and close to 400 urban populations. Among many results, we generate taxonomies of states and cities based on their similarities in word use; estimate the happiness levels of states and cities; correlate highly-resolved demographic characteristics with happiness levels; and connect word choice and message length with urban characteristics such as education levels and obesity rates. Our results show how social media may potentially be used to estimate real-time levels and changes in population-level measures such as obesity rates.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
