Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B2, 555-562, 2016
https://doi.org/10.5194/isprs-archives-XLI-B2-555-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
08 Jun 2016
TWEETS AND FACEBOOK POSTS, THE NOVELTY TECHNIQUES IN THE CREATION OF ORIGIN-DESTINATION MODELS
H. K. Malema1 and W. Musakwa2 1University of Johannesburg, Faculty of Engineering and Built Environment, Kingsway & University Road, Johannesburg
2Department of Town and Regional Planning ,University of Johannesburg, Cnr Joe Slovo Drive and Beit Streets Doornfontein
Keywords: Geolocation based services, Big data, Social media, Pattern analysis, Network movements, Origin-Destination models, Kriging, Transportation planning 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.
Conference paper (PDF, 1036 KB)


Citation: Malema, H. K. and Musakwa, W.: TWEETS AND FACEBOOK POSTS, THE NOVELTY TECHNIQUES IN THE CREATION OF ORIGIN-DESTINATION MODELS, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B2, 555-562, https://doi.org/10.5194/isprs-archives-XLI-B2-555-2016, 2016.

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