In contemporary urban planning, understanding the preferences of residents and visitors is most vital for effective city management and tourism planning. This study delves into the potential of harnessing social media data to gain insights into urban preferences with the aim of informing tourism planning practices. The research question investigates the feasibility of extracting meaningful insights from social media users’ activity, thus converting big data into actionable information for planners. The project's primary objective is to validate the hypothesis that social media data can reveal people's perception of city image, aligning with interview data from visiting tourists. The study aims to establish indicators of city image using big data from social media platforms and complementing it with qualitative interview data. By analysing changes in the popularity of landmarks over time, the research seeks to discern trends, ultimately informing tourism planning practices. Methodologically, the study utilizes a dataset of photos sourced from the Flickr, leveraging time stamps and geo-tagged information for temporal and spatial analysis. This approach enables the identification of popular circuits and the tracking of changes in attraction preferences over time. Furthermore, the study juxtaposes these findings with governmental policies and infrastructure developments to assess their impact on urban preferences. The results reveal valuable insights into the dynamic nature of urban preferences and highlight the correlation between governmental interventions and changes in tourism patterns. By discerning popular circuits and understanding visitor perceptions, planners can optimize resource allocation and enhance the overall tourism experience. This study contributes to the evolving field of urban planning by demonstrating the efficacy of integrating social media data into decision-making processes, thus facilitating more informed and responsive tourism planning practices.