USER-GENERATED DATA IN CULTURAL MAPPING: ANALYZING GOOGLE POINT OF INTEREST REVIEWS IN DUBLIN
Keywords: Urban Diversity, Spatial Data, Artificial Intelligence, Text Analytics, Google POI, Nationality, Dublin
Abstract. International migration is changing the social structure and cultural landscape of countries and big cities worldwide, especially in developed countries which are the target of job and asylum seekers. On the other hand, cultural diversity is becoming an important concept from different perspectives, such as boosting innovation and spatial segregation in urban planning and studies. Google point of interest (POI) data, as a commercial type of user-generated spatial data, is a secondary data source that can provide some information on the gender and nationality of reviewers, and this information can be used as a proxy indicator of cultural and background diversity. Yet, the potential application of the Google POI data has not been investigated in urban cultural and diversity measurement. In this study, we used artificial intelligence and text analytics methods through the NamSor API to identify the nationality and gender of Google POI reviewers in the Dublin Metropolitan Area. This study aims to highlight the potential application of spatial user-generated data in cultural mapping. The results are relatively consistent with official data in Ireland. Moreover, the results show that the number of male reviewers may be significantly higher than women reviewers, and this difference might be because of the gender digital divide. Finally, this paper discusses the potential challenges of using Google POI data and the implemented methodology and tools for cultural and diversity mapping and measurement. The proposed data and implemented methods in this study may have implications for other purposes in urban studies as well.