Investigating scientific collaboration networks in Iraq using cloud computing and data mining

The academic performance of Iraqi authors and institutions is an important aspect that needs to be investigated in the field of research. Special scientific criteria establish a researcher's level. These include citations, published articles, and others. In this study, the aim is to analyze the academic performance patterns of Iraqi authors and institutions in Google Scholar. Collaboration patterns between Iraqi scientists and universities were explored using sophisticated data collection and analysis techniques. A crawler that worked in parallel with Google Scholar was created with SerpApi, thus collecting amounts of scientist profile data stored in MongoDB Atlas. The data were processed using Spark within the Amazon Web Services (AWS) Cloud. Complex network analysis and Cytoscape software were used to comprehensively investigate the co-authorship networks of Iraqi scientists. In addition, a set of complex network criteria was applied to reveal patterns of cooperation. After visualizing the network diagram and analyzing the relationships between the nodes, the virtual nodes and communities in the network were identified, revealing critical insights into the cooperation patterns of Iraqi scientists and universities. The results have important implications for research and development policies in Iraq and demonstrate the power of complex network analysis to reveal valuable insights into academic research collaboration.