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The Role of Big Data in Understanding Urban Dynamics: Social Sensing, Mobility Patterns, and Place Connectivity during the COVID-19 Pandemic
- Park, Jaehee
- Advisor(s): Tsou, Ming-Hsiang
Abstract
In the era of Big Data, the ability to analyze large datasets from various sources has revolutionized the understanding of urban dynamics. This dissertation explores the transformative role of big geospatial data, focusing on social media and mobile footprint data, in examining urban behaviors and interactions during the COVID-19 pandemic. The first study develops a social sensing index using Twitter data to monitor place-based mental health issues, offering valuable insights for public health interventions. The second study utilizes mobile phone data to analyze human mobility patterns in San Diego and New York City, revealing significant socioeconomic disparities exacerbated by the pandemic. The third study introduces the Connectivity-Socioeconomic Index (CSI) to measure urban connectivity and segregation, providing urban planners with a tool to identify and address social equity challenges. This research demonstrates the potential of integrating diverse data sources to enhance urban planning and public health strategies, emphasizing the importance of big data in understanding complex urban systems and guiding policy development.Together, these studies demonstrate the significant role of big data in providing insights into urban dynamics, social sensing, mobility patterns, and place connectivity. The broader impact of this research on society includes the potential to enhance public health monitoring and intervention strategies. By using social media data to track mental health trends and mobility data to understand human movement patterns, public health officials can identify at-risk populations and areas, enabling more targeted and effective interventions. This research also informs urban planners and policymakers about the spatial dynamics of cities, helping to create more connected and equitable urban environments.
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