Examining Different Research Communities: Authorship Network
This work provides insights into research community structures for computer science domains, but it is incremental as it applies existing network analysis methods to new data.
The authors analyzed co-authorship networks from Google Scholar data (2000-2021) for Data Mining and Software Engineering, finding distinct network structures and small communities among influential authors in each domain.
Google Scholar is one of the top search engines to access research articles across multiple disciplines for scholarly literature. Google scholar advance search option gives the privilege to extract articles based on phrases, publishers name, authors name, time duration etc. In this work, we collected Google Scholar data (2000-2021) for two different research domains in computer science: Data Mining and Software Engineering. The scholar database resources are powerful for network analysis, data mining, and identify links between authors via authorship network. We examined coauthor-ship network for each domain and studied their network structure. Extensive experiments are performed to analyze publications trend and identifying influential authors and affiliated organizations for each domain. The network analysis shows that the networks features are distinct from one another and exhibit small communities within the influential authors of a particular domain.