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Twitter Sentiment Geographical Index Dataset.

Yuchen ChaiDevika KakkarJuan PalaciosSiqi Zheng
Published in: Scientific data (2023)
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.
Keyphrases
  • social media
  • deep learning
  • physical activity
  • high throughput
  • emergency department
  • machine learning
  • artificial intelligence
  • quality improvement
  • global health