Abstract Promoting well-being is one of the key targets of the Sustainable Development Goals at Roller 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 Intermittent Pre-Lubricated Catheters 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.