Culture Fingerprint: Identification of Culturally Similar Urban Areas Using Google Places Data

Autor(es)

Gubert, Fernanda R. ; Santos, Gustavo H. ; Delgado, Myriam ; Silver, Daniel ; Silva, Thiago H.

• Tipo de documento: Artigo Científico
• Fonte: SOCIAL NETWORKS ANALYSIS AND MINING, ASONAM 2024, PT II; v. 15212, p. 12-pg., 2025-01-01.

Resumo

This study investigates methods using a global data source, Google Places, to identify culturally similar urban areas without relying on difficult-to-access data like user preferences shown through checkins. We propose and assess a simple method requiring only information about place types and their frequency in the studied areas, and a more advanced method that enhances venue categories using Scenes Theory it helps us understand the cultural significance of everyday urban life. We tested our methods in 14 cities worldwide and all US states. The results suggest that a straightforward approach based on category frequencies can highlight major cultural differences. However, the Scenes Theory-based method provides a better understanding of cultural nuances, as the ones supported by survey data. (AU)

• Processo FAPESP: 23/00148-0 - SocialNet: sensoriamento social para alavancar novas tecnologias e aplicações para o desenvolvimento de sociedades urbanas
• Beneficiário: Thiago Henrique Silva
• Modalidade de apoio: Auxílio à Pesquisa - Regular