Modeling tourism using spatial analysis based on social media big data: a review

Chen Z and Rayner Alfred and Oliver Valentine Eboy (2021) Modeling tourism using spatial analysis based on social media big data: a review. In: International Conference on Computational Science and Technology, ICCST 2020, 29 - 30 August 2020, Pattaya, Thailand.

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Abstract

Since an ever-increasing part of the population makes use of social media in their day-to-day lives, social media data has been analyzed in many different disciplines. While there is a great deal of literature on the challenges and difficulties involving specific data analysis methods, there hardly exists research on analyzing the appropriate techniques used to handle different types of data for the purpose of social media analytics. To address this gap, we conducted an extended and structured literature analysis through which we identified challenges addressed and solutions proposed. The literature search revealed that three types of data that were least used for social media analytics that includes Bluetooth, WIFI and mobile roaming data. In contrast, other types of data have received more attention. Based on the results of the literature search, we discuss the most important challenges for researchers and present potential solutions. The findings are used to extend an existing framework on social media analytics. The article provides benefits for researchers and practitioners who wish to collect and analysis social media data.

Item Type:	Conference or Workshop Item (Paper)
Keyword:	Big data , Social media , Spatial analysis , Tourism
Subjects:	H Social Sciences > HA Statistics H Social Sciences > HF Commerce
Department:	FACULTY > Faculty of Computing and Informatics
Depositing User:	DG MASNIAH AHMAD -
Date Deposited:	23 Jul 2021 12:35
Last Modified:	23 Jul 2021 14:15
URI:	https://eprints.ums.edu.my/id/eprint/30008

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