Identifying a Supranational Image of Southeast Asia using Machine Learning

Main Article Content

Krantharat Sukanthong
Assoc. Prof. Viriya Taecharungroj, D.P.A.

Abstract

The core of place marketing and branding is the concept of place image which can be defined as a group’s or an individual’s perception towards a particular place. Images represent a simplification of a large number of associations and pieces of information connected with the places. A level of place image that requires further investigation is supranational image – a level of a place image that is larger than a country. Therefore, the purpose of this research is to introduce a new method to identify the supranational image of Southeast Asia (SEA). This new method can help identify a unified supranational image of SEA, to transfer image from stronger countries to weaker ones, and to create regional thematic products and services. This research uses a combination of Google Cloud Vision AI and a topic modelling algorithm, latent Dirichlet allocation (LDA) to analyse 50,000 Flickr photos of the 10 countries and to identify the image of SEA which comprises beautiful and diverse landscape, rich tropical nature, elegant historic and religious architecture, bustling city scenes, and cultural and recreational activities.

Article Details

How to Cite
Sukanthong, K., & Taecharungroj, V. (2021). Identifying a Supranational Image of Southeast Asia using Machine Learning. Journal of International Studies, Prince of Songkla University, 11(1), 215–252. Retrieved from https://so03.tci-thaijo.org/index.php/jis/article/view/252556
Section
Research Articles
Author Biography

Krantharat Sukanthong, MUIC, Mahidol University

MBA Student

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Appendix
Activities photos
AC1: https://www.flickr.com/photos/15368831@N00/3976204032
AC2: https://www.flickr.com/photos/88192491@N08/8797297908
AC3: https://www.flickr.com/photos/34534185@N00/6605022485
AC4: https://www.flickr.com/photos/53836467@N07/9032638107
AC5: https://www.flickr.com/photos/65548818@N00/16301625821
AC6: https://www.flickr.com/photos/54238729@N07/14346024054
Architecture photos
AR1: https://www.flickr.com/photos/17291033@N00/4839832214
AR2: https://www.flickr.com/photos/71048973@N00/12842517294
AR3: https://www.flickr.com/photos/88151946@N00/33773761641
AR4: https://www.flickr.com/photos/31190896@N08/6499612057
AR5: https://www.flickr.com/photos/126971360@N02/24725835765
AR6: https://www.flickr.com/photos/69862881@N00/8883443568
Nature photos
NA1: https://www.flickr.com/photos/22451301@N00/10639019666
NA2: https://www.flickr.com/photos/89604217@N04/8159117102
NA3: https://www.flickr.com/photos/46133228@N02/34039009110
NA4: https://www.flickr.com/photos/58989164@N02/6283123074
NA5: https://www.flickr.com/photos/106254613@N05/10492959275
NA6: https://www.flickr.com/photos/39415470@N02/8087489499
City photos
CI1: https://www.flickr.com/photos/44124447497@N01/400140019
CI2: https://www.flickr.com/photos/25725480@N00/4825899210
CI3: https://www.flickr.com/photos/26781577@N07/11512501443
CI4: https://www.flickr.com/photos/75212875@N02/36019310096
CI5: https://www.flickr.com/photos/52741348@N02/30197582287
CI6: https://www.flickr.com/photos/45928922@N03/8509721095
Landscape photos
LA1: https://www.flickr.com/photos/88192491@N08/8786656659
LA2: https://www.flickr.com/photos/75212875@N02/35823805414
LA3: https://www.flickr.com/photos/147711984@N08/27841515309
LA4: https://www.flickr.com/photos/100635695@N04/23029314679
LA5: https://www.flickr.com/photos/112649395@N05/40295658672
LA6: https://www.flickr.com/photos/31366043@N03/14862374415