Twitter Sentiment Geographical Index Dataset

被引:3
|
作者
Chai, Yuchen [1 ]
Kakkar, Devika [2 ]
Palacios, Juan [1 ]
Zheng, Siqi [1 ]
机构
[1] MIT, Sustainable Urbanizat Lab, Cambridge, MA 02139 USA
[2] Harvard Univ, Ctr Geog Anal, Cambridge, MA 02138 USA
关键词
HEALTH; INCOME; WORK;
D O I
10.1038/s41597-023-02572-7
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Promoting well-being is one of the key targets of the Sustainable Development Goals at the United Nations. Many national and city governments worldwide are incorporating Subjective Well-Being (SWB) indicators into their agenda, to complement traditional objective development and economic metrics. In this study, we introduce the Twitter Sentiment Geographical Index (TSGI), a location-specific expressed sentiment database with SWB implications, derived through deep-learning-based natural language processing techniques applied to 4.3 billion geotagged tweets worldwide since 2019. Our open-source TSGI database represents the most extensive Twitter sentiment resource to date, encompassing multilingual sentiment measurements across 164 countries at the admin-2 (county/city) level and daily frequency. Based on the TSGI database, we have created a web platform allowing researchers to access the sentiment indices of selected regions in the given time period.
引用
收藏
页数:12
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