A big-data analytics method for capturing visitor activities and flows: the case of an island country
Source of Publication
Information Technology and Management
© 2019, Springer Science+Business Media, LLC, part of Springer Nature. Understanding how people move from one location to another is important both for smart city planners and destination managers. Big-data generated on social media sites have created opportunities for developing evidence-based insights that can be useful for decision-makers. While previous studies have introduced observational data analysis methods for social media data, there remains a need for method development—specifically for capturing people’s movement flows and behavioural details. This paper reports a study outlining a new analytical method, to explore people’s activities, behavioural, and movement details for people monitoring and planning purposes. Our method utilises online geotagged content uploaded by users from various locations. The effectiveness of the proposed method, which combines content capturing, processing and predicting algorithms, is demonstrated through a case study of the Fiji Islands. The results show good performance compared to other relevant methods and show applicability to national decisions and policies.
Springer New York LLC
Big data, Data analytics, Decision making, Location flows, Smart city initiatives
Miah, Shah Jahan; Vu, Huy Quan; and Gammack, John, "A big-data analytics method for capturing visitor activities and flows: the case of an island country" (2019). All Works. 40.
Indexed in Scopus
Open Access Type
Green: A manuscript of this publication is openly available in a repository