Titlebook: Information and Communication Technologies in Tourism 2022; Proceedings of the E Jason L. Stienmetz,Berta Ferrer-Rosell,David Massi Confere

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書目名稱Information and Communication Technologies in Tourism 2022讀者反饋學(xué)科排名

alliance

Video Games as a Media for Tourism Experiencemagery and a sense of presence to the location. The methodology proposed for this study is a quantitative approach, using survey questionnaire as a tool. Two sampling method is proposed. The first is to use players of location-based games as the population, and randomly take the sample. The second m

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Beyond Influencer Credibility: The Power of Content and Parasocial Relationship on Processing Socialration Likelihood Model (ELM) as a framework, this study illuminates consumers’ interaction with the SMI destination marketing campaign and extends prior studies in understanding the importance of SMI content and parasocial relationship as a significant tool for future destination marketing.

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tensions, but we?also identify specific applications to the shallow water equations?of interest in this book. The chapter is concluded with two examples that highlight the key point of very high-order methods; that is, for small errors high-order ADER methods are orders-of-magnitude more efficient t

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400, 600, 800, and 1000 functional regions based on Schaefer atlas in the Montreal Neurological Institute (MNI) template. To evaluate these six versions of?FE models, we subjected them to three typical concussive impacts including frontal, lateral and rear impacts based on National Football League (

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Mattia Rainoldi,Arne Van den Winckel,Joanne Yu,Barbara Neuhofer representation of the target variable through stratified sampling. The logistic regression model is then trained and its predictive accuracy evaluated across varying feature sets, demonstrating the significance of feature selection on model effectiveness. The proposed method for feature selection i

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Dimitrios Buhalis,Nurshat Karatay 90.33% on our validation dataset. We apply this classifier on a sample of 1.5M tweets retrieved from the #Election2020 dataset and perform an n-gram analysis of the classification results, using s-BERT embeddings and DBSCAN clustering to reveal topics of interest to communities of different politic