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A big-data analytics method for capturing visitor activities and flows: the case of an island country

Abstract

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.

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Notes

  1. Design science research is a pragmatic research paradigm that promotes the development and evaluation of information systems artifacts to solve real world issues [18, 19].

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Correspondence to Shah Jahan Miah.

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Miah, S.J., Vu, H. & Gammack, J. A big-data analytics method for capturing visitor activities and flows: the case of an island country. Inf Technol Manag 20, 203–221 (2019). https://doi.org/10.1007/s10799-019-00303-2

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  • DOI: https://doi.org/10.1007/s10799-019-00303-2

Keywords

  • Big data
  • Decision making
  • Smart city initiatives
  • Data analytics
  • Location flows