Web Application Development for Expertise Search and Research Collaboration of Chiang Mai University's Researchers Using Text Mining

Abstract

© 2020 IEEE. Exploring university researchers with expertise related to various academic topics often takes a long time, and the use of different selection factors, such as the publication number or citations, causes inaccurate findings and tends to miss the targets that are set by the university or faculty's research authorities. This study aims to create a decision support application for exploring the expertise and research collaboration of researchers in Chiang Mai University by using the Spyder and Visual Studio Code from Anaconda to extract data from the Scopus database; create web application from the Python Flask Framework and HTML by working with MySQL database to store data according to Text Mining and Bootstrap. The web application development facilitates university executives or faculty's research department regarding the managerial decision in order to search for the expertise researchers according to the interested academic topics. The web results show the expertise of each researcher and the faculty's expertise; and the list of institutes that have collaborated with an individual researcher in Word Cloud format. Concerning the scoring criteria, different factors are used, such as the number of citations, the SJR values from the data sources published in the Scopus database, and the number of publications in each topic.