Title
A big-data analytics method for capturing visitor activities and flows: the case of an island country
Source of Publication
Information Technology and Management
Abstract
© 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.
Document Type
Article
First Page
203
Last Page
221
Publication Date
12-1-2019
DOI
10.1007/s10799-019-00303-2
Recommended Citation
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). Scopus Indexed Articles. 494.
https://zuscholars.zu.ac.ae/scopus-indexed-articles/494