Online data reliability for monitoring tourism activities in cities

Studying the spatial structure of destinations has long been considered an important topic on tourism research. Researchers focus their attention on the analysis of tourism consumption and production. Recent studies found that non-traditional data, either from social media or peer-to-peer digital platforms, is useful for managing and monitoring tourism activities on dynamic destinations such as cities. However, more research is needed to address data reliability since it is important to understand the strengths and limitations of this novel data. This paper compares visitor counts to Lisbon city identified by their digital footprints on social media (i.e., visitors’ geotagged photos from Flickr) with official hotel occupancy rates, as well as the accommodation supply from Airbnb listings with local accommodation official statistics. Findings demonstrated that the number of visitors identified by their digital footprints matches relatively well the visitation pattern reproduced by hotel occupancy rates. Datasets representing the accommodation supply uncovered the spatial concentration of local lodgings, not exclusively in the well-known tourist areas. Despite the strong correlation between datasets, there are some areas where the lodging counts deviate significantly, as we move from the periphery to tourism cores. Results showed the value of data from social media and peer-to-peer digital platforms as proxy for monitoring city tourism activities.