Title

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

ORCID Identifiers

0000-0002-3783-8769

Document Type

Article

Source of Publication

Information Technology and Management

Publication Date

12-1-2019

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.

ISSN

1385-951X

Publisher

Springer New York LLC

Volume

20

Issue

4

First Page

203

Last Page

221

Disciplines

Computer Sciences

Keywords

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

Scopus ID

85066468344

Indexed in Scopus

yes

Open Access

yes

Open Access Type

Green: A manuscript of this publication is openly available in a repository

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