Academic Articles by Chula Engineering Professors and Students Receive the JDR Award for the Most Cited Paper 2024 in Japan 

Academic articles written by Chula Engineering Faculty and students have received the JDR Annual Awards and were published in the Journal of Disaster Research, Issue 20(1), February 2025. The Journal of Disaster Research (JDR) editorial office held the award ceremony on December 20, 2024, at Gakushi Kaikan, Tokyo, Japan. 

Assoc. Prof. Dr. Natt Leelawat, Assistant to the Dean of the Faculty of Engineering and a lecturer in the Department of Industrial Engineering, Chula Faculty of Engineering, was invited to receive the JDR Award for the Most Cited Paper of 2024 for the academic article titled “Twitter Sentiment Analysis on Bangkok Tourism During the COVID-19 Situation Using the Support Vector Machine Algorithm.” 

This academic article was published in 2021 and was co-authored by: 

• Mr. Thanapat Sontayasara, Mr. Arnon Promjun, and Mr. Napat Seelpipat, graduates of the Bachelor of Engineering program from the Department of Industrial Engineering. 
• Dr. Kumpol Saengtabtim, postdoctoral researcher, Department of Industrial Engineering. 
• Prof. Dr. Jing Tang, lecturer at the International School of Engineering. 
• Assoc. Prof. Dr. Natt Leelawat, lecturer in the Department of Industrial Engineering. 

Abstract: Twitter Sentiment Analysis on Bangkok Tourism During the COVID-19 Situation Using the Support Vector Machine Algorithm

In the year 2020, SARS-CoV-2, the virus behind the coronavirus disease (COVID-19) pandemic, affected many lives and businesses worldwide. COVID-19, which originated in Wuhan City, China, at the end of December 2019, spread over the entire world in approximately four months. By October 2020, approximately 20 million people were infected and millions had died from this disease. Many health organizations such as the World Health Organization and Centers for Disease Control and Prevention made COVID-19 their primary focus. Many industries, especially, the tourism industry, were affected by the pandemic as many flight and hotel reservations were canceled. Thailand, a country considered one of the world’s most popular tourist destinations, suffered much losses because of this pandemic. Many events and travel bookings were canceled and/or postponed. Many people expressed their views and emotions related to this situation over social media, which is considered a powerful media for spreading news and information. In this research, the views of people who were planning to travel to Bangkok, the capital city and most popular destination in Thailand, were retrieved from Twitter for the dates between April 3 and 30, 2020, the period during which the country underwent nationwide lockdown. Sentiment analysis was performed using the support vector machine algorithm. The results showed 71.03% classification accuracy based on three sentiment classifications: positive, negative, and neutral. This study could thus provide an insight into travelers’ opinions and sentiments related to the tourism business. Based on the significant terms in each sentiment extracted, strengths and weaknesses of each tourism issue could be obtained, which could be used for making recommendations to the related tourism organizations. 

The article was published in the Journal of Disaster Research, Vol. 16, No. 1, pages 24-30. Read it here: https://doi.org/10.20965/jdr.2021.p0024 
Read news about the JDR Annual Awards ceremony in the Journal of Disaster Research: http://doi.org/10.20965/jdr.2025.p0003
Message from Awardees: https://doi.org/10.20965/jdr.2025.p0006

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