Analyzing Interdisciplinary Research Using Co-Authorship Networks

With the advancement of scientific collaboration in 20th century, researchers started collaborating many research areas. Researchers and scientists no longer remain solitary individuals; instead, they collaborate to advance fundamental understandings topics. Various bibliometric methods are used quantify among communities. Among these different methods, co-authorship method is one most verifiable or analyze collaboration. In this research, initial study has been conducted interdisciplinary (IDR) activities computer science domain. The ACM classified fields. We selected Journal Universal Computer Science (J.UCS) for experimentation purposes. J.UCS first that addresses a complete topic. Using data, network researcher up 2nd level was developed. Then analyzed find Additionally, results also visualized comprehend categories. A whole working web-based system developed, forced directed graph technique implemented understand IDR trends Finally, values between categories computed It found “Artificial Intelligence” “Information Storage Retrieval”, “Natural Language Processing Information “Human-Computer Interface” “Database Applications” were overlapping areas by acquiring an score 0.879, 0.711, 0.663, respectively.