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Article Citation - WoS: 12Citation - Scopus: 16A 30-Year Journey of Hospitality and Tourism Research: a Comprehensive Topic Modeling Analysis(Emerald Group Publishing Ltd, 2024) Kurt, Senol; Assefa, Feven Zewdie; Tuzlukaya, Sule Erdem; Karatepe, Osman M.PurposeThe purpose of this study is to provide an overview of the research conducted on hospitality and tourism articles published in Q1 category journals from 1990 to 2023. This study also aims to measure the topic prevalence in selected journals throughout the years, their change over time and similarities of journals.Design/methodology/approachLatent dirichlet allocation algorithm is used as a topic modeling method to identify and analyze topics in hospitality and tourism research over the past 30 years.FindingsThe results of the study indicate that hospitality and tourism research has recently focused on topics such as employee behavior, customer satisfaction, online reviews, medical tourism and tourist experience. However, the results also indicate a negative trend in topics such as hotel management, sustainability, profession, economic growth and tourist destination.Practical implicationsThis study can be used to examine the evolution of research patterns over time, find hot and cold themes and uncover untapped or understudied areas. This can aid academics in their investigations and practitioners in making sound strategic decisions.Originality/valueThis study contributes to the existing literature by providing a new approach and comprehensive analysis of hospitality and tourism research topics. It delineates an overview of the progression of hospitality and tourism research over the past 30 years, identifies the trending topics and explores the potential impacts that these identified topics may have on future studies.Article Citation - WoS: 11Citation - Scopus: 17Student Engagement Research Trends of Past 10 Years: a Machine Learning-Based Analysis of 42,000 Research Articles(Springer, 2023) Gurcan, Fatih; Erdogdu, Fatih; Cagiltay, Nergiz Ercil; Cagiltay, KursatStudent engagement is critical for both academic achievement and learner satisfaction because it promotes successful learning outcomes. Despite its importance in various learning environments, research into the trends and themes of student engagement is scarce. In this regard, topic modeling, a machine learning technique, allows for the analysis of large amounts of content in any field. Thus, topic modeling provides a systematic methodology for identifying research themes, trends, and application areas in a comprehensive framework. In the literature, there is a lack of topic modeling-based studies that analyze the holistic landscape of student engagement research. Such research is important for identifying wide-ranging topics and trends in the field and guiding researchers and educators. Therefore, this study aimed to analyze student engagement research using a topic modeling approach and to reveal research interests and trends with their temporal development, thereby addressing a lack of research in this area. To this end, this study analyzed 42,517 peer-reviewed journal articles published from 2010 to 2019 using machine learning techniques. According to our findings, two new dimensions, "Community Engagement" and "School Engagement", were identified in addition to the existing ones. It is also envisaged that the next period of research and applications in student engagement will focus on the motivation-oriented tools and methods, dimensions of student engagement, such as social and behavioral engagement, and specific learning contexts such as English as a Foreign Language "EFL" and Science, Technology, Engineering and Math "STEM".
