A Bibliometric Analysis Tourism Data Mining from 2012 to 2022

Abstract

Data mining is the process of collecting big data and discovering research patterns on a topic involving machine learning methods, statistics, and database systems. This paper presents a bibliometric analysis tourism data mining from 2012 to 2022. The analysis used in extracting data that has been collected uses bibliometric analysis approach. Bibliometric analysis is used to analyze large data which is classified into several groups. These data are grouped into documents based on data type, documents based on subject, documents based on country of origin, and total publications each year i.e.: from 2012 to 2022. The purpose of data mining bibliometric analysis on tourism is to find out the development of research on tourism and find out the trends that are currently happening in data mining for tourism and also know the development of publications, countries with the total publications, and the appearance of keywords in the data.  707 documents were found and we finally choose 491 documents. These data were taken from the Scopus database on November 18, 2022, which is a large and complete database. The tools used in this bibliometric analysis are Harzing's Publish or Perish for extracting data from Scopus databases and VOS Viewer for data visualization and further used for citation and metrics analysis. The results of the analysis show that there are 2 keywords that have the most total networks, namely "Tourism" and "Data Mining" which were published around 2019. As well as keywords that are rarely used, namely "Text Mining" and "Social Network". The country with the highest number of publications is China with a total of 105 published documents. In Overlay Visualization research trends in Data Mining Tourism recently are "Sustainable Tourism", "Conservation", Big Data", and "Online Review" which show bright nodes in Overlay Visualization.