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All Journal Journal of Applied Data Sciences International Journal Research on Metaverse
Kim, Jong Il
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management

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Survey Opinion using Sentiment Analysis Hariguna, Taqwa; Sukmana, Husni Teja; Kim, Jong Il
Journal of Applied Data Sciences Vol 1, No 1: SEPTEMBER 2020
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v1i1.10

Abstract

Sentiment analysis or opinion mining is a computational study of the opinions, judgments, attitudes, and emotions of a person towards an entity, individual, issue, event, topic, and attributes. This task is very challenging technically but very useful in practice. For example, a business always wants to seek opinion about its products and services from the public or the consumers. Additionally, potential consumers want to learn what users think they have when using a service or purchasing a product. To get public opinion on food habits, ad strategies, political trends, social issues and business policy, this is a very critical factor. This paper will explain a survey of key sentiment-extraction approaches.
Exploring the Impact of Virtual Reality Experiences on Tourist Behavior and Perceptions Sukmana, Husni Teja; Kim, Jong Il
International Journal Research on Metaverse Vol. 1 No. 2 (2024): Regular Issue September
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/ijrm.v1i2.8

Abstract

This study explores the impact of virtual reality (VR) experiences on tourist behavior and perceptions, utilizing logistic regression and analysis of variance (ANOVA) to understand these relationships. The logistic regression analysis revealed that VR experience (coefficient = 0.432, p = 0.020) significantly enhances the likelihood of being a tourist. Demographic factors such as gender (coefficient = -0.512, p = 0.018), income (coefficient = -0.301, p = 0.001), and age (coefficient = 0.298, p = 0.003) also play crucial roles: females and higher-income individuals are less likely to be tourists, while older individuals are more likely to travel. ANOVA results indicated significant differences in emotional responses (EMO1: F = 6.40, p = 0.012; EMO2: F = 4.63, p = 0.032; EMO3: F = 7.77, p = 0.006; EMO4: F = 5.77, p = 0.017), flow states (FLOW1: F = 12.21, p = 0.001; FLOW2: F = 20.39, p < 0.001; FLOW3: F = 17.38, p < 0.001; FLOW4: F = 14.52, p < 0.001), and intentions to visit (INT2: F = 7.79, p = 0.006; INT4: F = 4.61, p = 0.032) based on VR experience. These findings suggest that VR significantly influences emotional and cognitive states, fostering engagement, satisfaction, and increased intentions to visit real-world destinations. The results underscore the potential of VR as a powerful tool in tourism marketing, capable of driving tourism interest and behavior. Future research should investigate the long-term effects of VR on tourist behavior and consider cultural and technological advancements to further optimize VR's application in tourism. This study offers actionable insights for tourism marketers to develop targeted, effective, and immersive VR promotional strategies.
Co-Authors Husni Teja Sukmana Taqwa Hariguna