Investigating social media spatiotemporal transferability for transport

Social Media have increasingly provided data about the movement of people in cities making them useful understanding daily life different geographies. Particularly for travel analysis is when users allow (voluntarily or not) tracing their using geotagged information communication with these online platforms. In this paper we use tweets from 10 European Union and United States America to extract spatiotemporal patterns, study differences commonalities among cities, explore nature user location recurrence. The here shows distinction between residents tourists fundamental development city-wide models. Identification repeated rates (recurrence) can be used define activity spaces. Differences similarities across geographies emerge terms local distributions but also worldwide reach explored here. comparison temporal signature non-geotagged similar that capture essence city rhythms