Cultural mapping provides a simple and direct visual tool to identify and analyze different aspects of culture from a local perspective. By adopting traditional methods (for example, a large-scale survey), building cultural maps is an expensive process in terms of cost, human resources, and time. This is because it requires the accurate collection and analysis of data.

Location-based social networks (LBSNs) have recently emerged, presenting an unprecedented opportunity to study large-scale user behavioral data. This paper proposes an approach for participatory cultural mapping based on LBSN analysis.

Despite the enormous theoretical potentialities of LBSNs, their analysis is generally not straightforward. Cultural mapping addresses specific challenges, as only indigenous and local people are eligible to represent local culture. Therefore, check-ins play a critical but also ambiguous role. The proposed approach consists of four steps, including data collection at a global state, local user detection, cultural features extraction, and visualization through clustering.

Cultural mapping is definitely an interesting topic that is evolving with the reference technology. Indeed, emerging technologies are outlining new, exciting perspectives for cultural mapping. I enjoyed reading this paper even though, considering the current technological trends, I would have expected a more open approach eventually oriented to the semantic web.