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Twitter Sentiment Geographical Index Dataset
Yuchen Chai1, Devika Kakkar2, Juan Palacios1
1Sustainable Urbanization Lab, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
Scientific Data
|October 9, 2023
Summary
This study introduces the Twitter Sentiment Geographical Index (TSGI), a global database of geotagged tweets. TSGI offers location-specific sentiment data to help measure Subjective Well-Being (SWB) and inform policy.
Area of Science:
- Computational social science
- Geospatial analysis
- Natural language processing
Background:
- Subjective Well-Being (SWB) is a key target for global development.
- Governments increasingly use SWB indicators alongside traditional metrics.
- A need exists for large-scale, location-specific sentiment data.
Purpose of the Study:
- Introduce the Twitter Sentiment Geographical Index (TSGI) database.
- Provide a comprehensive, open-source resource for sentiment analysis.
- Facilitate research on the geographical distribution of public sentiment.
Main Methods:
- Utilized deep learning and natural language processing.
- Analyzed 4.3 billion geotagged tweets globally since 2019.
- Developed multilingual sentiment measurements at the admin-2 level.
Main Results:
- Created the TSGI, the most extensive Twitter sentiment database to date.
- Covered 164 countries with daily sentiment frequency.
- Established a web platform for accessing TSGI data.
Conclusions:
- TSGI offers a novel tool for understanding geographical sentiment.
- The database supports research into Subjective Well-Being (SWB) indicators.
- Open access to TSGI data promotes wider scientific inquiry.
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