Twitter Sentiment Geographical Index Dataset
Author(s)
Chai, Yuchen; Kakkar, Devika; Palacios, Juan; Zheng, Siqi
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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.
Date issued
2023-10-09Publisher
Springer Science and Business Media LLC
Citation
Chai, Y., Kakkar, D., Palacios, J. et al. Twitter Sentiment Geographical Index Dataset. Sci Data 10, 684 (2023).
Version: Final published version
ISSN
2052-4463
Keywords
Library and Information Sciences, Statistics, Probability and Uncertainty, Computer Science Applications, Education, Information Systems, Statistics and Probability
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