Urban Tapestry: Weaving Geospatial Data with Social Sentiment to Understand Crime Patterns

In the pursuit of creating safer, more resilient urban spaces, this research addresses the fundamental question: How does the interplay between urban design and public sentiment shape crime trends and community safety? By merging geospatial analysis of land use with sentiment analysis from social media, this study explores the profound influence of urban landscapes on both crime occurrences and societal perceptions. The analysis begins with a comprehensive set of urban data to delineate crime hotspots and uncover correlations with the urban form, shedding light on the 'when' and 'where' of crime incidents. Complementary to this is the sentiment analysis of social media content, which taps into the community's pulse on crime and safety, offering a deeper understanding of the 'how' and 'why' behind public reactions—dimensions often underrepresented in traditional crime analysis. Despite limitations in geotagged data, innovative natural language processing techniques, aim to approximate spatial sentiment distributions. This bifocal approach not only pinpoints areas of concern but also clarifies the public's response to crime, which could steer policy and urban planning towards impactful interventions. The integration of diverse data types is essential for a holistic view, one that balances quantitative crime data with the qualitative nuances of human experience. The presentation undertakes a deep dive into how data-driven insights can empower data and geospatial professionals within research, libraries and archives to craft narratives that blend numbers with nuance, aiding in the design of safer, more resilient urban space