Abstract
Social media and big data have emerged to be a useful source of information that can be used for planning purposes,
particularly transportation planning and trip-distribution studies. Cities in developing countries such as South Africa often
struggle with out-dated, unreliable and cumbersome techniques such as traffic counts and household surveys to conduct
origin and destination studies. The emergence of ubiquitous crowd sourced data, big data, social media and geolocation
based services has shown huge potential in providing useful information for origin and destination studies. Perhaps such
information can be utilised to determine the origin and destination of commuters using the Gautrain, a high-speed railway
in Gauteng province South Africa. To date little is known about the origins and destinations of Gautrain commuters.
Accordingly, this study assesses the viability of using geolocation-based services namely Facebook and Twitter in mapping
out the network movements of Gautrain commuters. Explorative Spatial Data Analysis (ESDA), Echo-social and ArcGis
software were used to extract social media data, i.e. tweets and Facebook posts as well as to visualize the concentration of
Gautrain commuters. The results demonstrate that big data and geolocation based services have the significant potential to
predict movement network patterns of commuters and this information can thus, be used to inform and improve
transportation planning. Nevertheless use of crowd sourced data and big data has privacy concerns that still need to be
addressed.