Urban Cultural Signature with Web Data: A Case Study with Google Places Venues

Providing knowledge about the characteristics of diverse cultural groups worldwide and identifying cultural similarities between their respective occupation regions can yield significant economic and social benefits. However, much of the existing research in this field relies on user behavior data, which may limit scalability and generalization due to the difficulty in obtaining such data. To address this, our work focuses on extracting venue data from Google Places and proposing a methodology based on the Scenes concept to enrich this dataset for generating cultural signatures of urban areas. This approach also considers the influence of different area sizes. Using Curitiba, Brazil, and Chicago, USA, as case studies, the results demonstrate that the proposed method can identify cultural similarities between regions while supporting an area-division strategy for analyzing cities across different countries. The findings show consistency, as evidenced by the segmentation of Curitiba and Chicago into culturally distinct clusters. This highlights the societal benefits of the proposal, such as location recommendations based on cultural criteria and real-time service validation.