https://doi.org/10.1140/epjds/s13688-026-00657-y
Research
Understanding the spatial and temporal impact of global events through large-scale social media data
Department of Information Systems, University of Münster, Leonardo-Campus 3, 48149, Münster, North Rhine-Westphalia, Germany
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Received:
1
August
2025
Accepted:
10
April
2026
Published online:
17
April
2026
Abstract
Large-scale urban social media data can provide substantial insights into the real-time development of cities around the globe, illuminating phenomena such as gentrification, urban decay, and resilience to major adverse events. This study utilizes a dataset of over 147.8 million georeferenced tweets from multiple cities to demonstrate their potential for analyzing the emotional and temporal impacts of major events, including the U.S. presidential elections and the Covid-19 pandemic. By employing a sentiment indicator and an anxiety indicator, we highlight the importance of establishing robust baselines that are not only city-specific but also long-term, population-based, and user-based. We demonstrate the value of integrating georeferenced data with long-term analysis to uncover spatial and temporal patterns in public emotional responses, offering new perspectives on the dynamics of crises, such as climate change, and societal resilience.
Key words: Large-scale analysis / Urban data / Social media / Event analysis
Handling Editor: Matthew Williams
© The Author(s) 2026
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