Twitter Sentiment Geographical Index Dataset
Name
s41597-023-02572-7.pdf
Size
2.3 MB
Format
Adobe PDF
Checksum (MD5)
7c324f0a6c5411ace708db982871e8cf
Author(s)
Chai, Yuchen
Kakkar, Devika
Palacios, Juan
Zheng, Siqi
Date Issued
October 9, 2023
Publisher
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
Abstract
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.
Subjects
Library and Information Sciences
Statistics, Probability and Uncertainty
Computer Science Applications
Education
Information Systems
Statistics and Probability
Terms of Use
Creative Commons Attribution
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1038/s41597-023-02572-7
