Google Scholar is one of the top search engines to access research articles across multiple disciplines for scholarly literature. Google Scholar’s advanced search option gives the privilege to extract articles based on phrases, publisher name, author 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 identifying links between authors via co-authorship network. We examined co-authorship networks for each domain and studied their network structure. Extensive experiments are performed to analyze publication trends and identify influential authors and affiliated organizations for each domain. The network analysis shows that the network’s features are distinct from one another and exhibit small communities within the influential authors of a particular domain.