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This study aims to use social media data mining to revitalize and support existing urban infrastructure monitoring strategies by extracting valuable insights from public opinion, as current strategies struggle with issues such as adaptability to changing conditions, public engagement and cost effectiveness.

Twitter messages or “Tweets” about public infrastructure in the Philippines were gathered and analyzed to discover reoccurring concerns in public infrastructure, emerging topics in public debates and the people’s general view of infrastructure services.

This study proposes a topic model for extracting dominating subjects from aggregated social media data, as well as a sentiment analysis model for determining public opinion sentiment toward various urban infrastructure components.

The findings of this study highlight the potential of social media data mining to go beyond the limitations of traditional data collection techniques, as well as the importance of public opinion as a key driver for more user-involved infrastructure management and as an important social aspect that can be used to support planning and response strategies in routine maintenance, preservation and improvement of urban infrastructure systems.

Adequate, reliable, and efficient urban infrastructure systems (UIS) are fundamental to sustainable development, social mobility, and economic vitality. As communities continuously rely on basic infrastructure services to support their daily communal functions, major components of UIS are subject to heavy use, and thus rapidly deteriorate over time; hence, it is critical that efficient infrastructure management strategies practices are in place. As current strategies remain confronted with various limitations including adaptability to changing conditions, lack of public engagement, and cost-effectiveness, this study explores social media data mining as an approach to revitalise and support current urban infrastructure monitoring strategies by extracting valuable insights from public opinion. Twitter messages or ‘Tweets’ pertaining to public infrastructure in The Philippines were collected and analysed to identify recurring issues in public infrastructure, emerging topics in public discussions, and the overall perception of the public on infrastructure services. This study presents a topic model that extracts dominant topics from aggregated social media data and a sentiment analysis model that determines public opinion sentiment in relation to different urban infrastructure components. The findings of this study highlight the potential of social media data mining to surpass the limits of conventional data collection techniques and the importance of public opinion as a key driver for a more user-involved decision-making in infrastructure management and as an important social aspect that can be utilised to support planning and response strategies in routine maintenance, preservation, and improvement of UIS.