Abstract
The study of commuters’ origins and destinations (O_D) promises to assist transportation planners with prediction models to
inform decision making. Conventionally O_D surveys are undertaken through travel surveys and traffic counts, however
data collection for these surveys has historically proven to be time consuming and having a strain on human resources, thus a
need for an alternative data source arises. This study combines the use social media data and geographic information systems
in the creation of a model for origin and destination surveys. The model tests the potential of using big data from Echo echo
software which contains Twitter and Facebook data obtained from social media users in Gauteng. This data contains geolocation
and it is used to determine origin and destination as well as concentration levels of Gautrain commuters. A krigging
analysis was performed on the data to determine the O-D and concentration levels of Gautrain users. The results reveal the
concentration of Gautrain commuters at various points of interest that is where they work, live or socialise. The results from
the study highlight which nodes attract the most commuters and also possible locations for the expansion for Gautrain.
Lastly, the study also highlights some weakness of crowdsourced data for informing transportation planning. (208)