A Network Analysis Approach to Comparing Collaboration Among Researchers at Universiti Putra Malaysia

Abstract

This study aims to analyze research collaboration within the Department of Mathematics and Statistics in Universiti Putra Malaysia in two distinct periods: 2020–2021 and 2022–2023. The analysis employs social network analysis and graph theory concepts, focusing on centrality measures such as degree, closeness, betweenness, and eigenvector centralities. This study investigates changes in research collaboration between the two periods in terms of centrality measures and identifies factors that influence their values.This study investigates three main research questions. First, it examines how to effectively model research collaborations among mathematicians. Second, it explores how centrality measures in collaboration networks, such as degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality, can be used to predict the most influential mathematicians. Finally, it analyzes changes in collaboration networks between 2020–2021 and 2022–2023. The findings may offer insights into enhancing future collaborative strategies and fostering a more connected and productive research environment.