The Analysis of Tourism Attitudes using Natural Language Processing Techniques: A Case of Malaysian Tourists

Md Tareq Bin Hossain; Ruchdee Binmad

doi:10.69650/ahstr.2024.1152

Authors

Md Tareq Bin Hossain Thammasat Business School, Tha Prachan, Bangkok, 10200, Thailand
Ruchdee Binmad Research Center for Business Intelligence and Analytics, Faculty of Management Sciences, Prince of Songkla University, 90110, Thailand

DOI:

https://doi.org/10.69650/ahstr.2024.1152

Keywords:

Sentiment analysis, Topic modeling, COVID-19, Tourist’s attitudes, Malaysian Tourists

Abstract

The spread of COVID-19 has had a significant impact on all facets of the global tourism sector, particularly in Thailand, one of the world’s leading travel destinations. At the height of the epidemic, many countries imposed a nationwide lockdown, prohibiting all citizens from leaving the country and all foreign tourists from entering. This led to a global shutdown that significantly affected the daily lives of billions of people and seriously impacted the travel and tourism industry. After a two-year hiatus due to the epidemic, the situation eased and the lockdown restrictions were lifted. An interesting question is how visitors’ attitudes and preferences changed when compared to the time before the outbreak. This study attempts to answer this question by focusing on Malaysian visitors’ attitudes and perceptions toward destinations in southern Thailand. The study examines the perceptions of Malaysian Twitter (now X) users from three areas in Malaysia; Kedah, Perlis, and Kuala Lumpur, by employing Natural Language Processing (NLP) techniques such as sentiment analysis and topic modeling. Then, tweet data before and after the lockdowns were gathered, analyzed, and compared. For sentiment analysis, it was found that, when neutral tweets were disregarded, results both before and after the COVID-19 lockdowns revealed that the attitudes conveyed by Malaysian tourists were overall positive especially a territory and a state that are more far away from Thailand, i.e., Kuala Lumpur and Kedah. The results from the topic modeling analysis showed a meaningful distinction between before and after the COVID-19 lockdowns. Practical suggestions are offered for tourism policymakers to identify and address both the strengths and weaknesses of tourism development in Southern Thailand.

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