This paper describes a pipeline to identify author adoption trends of software or methodologies using biomedical literature searches. Cavatica is a multi-network analysis pipeline for PubMed and PubMed Central (PMC) search results based on a heterogeneous network that combines papers and their authors; each unique paper or author is represented by a node in the network. Using Cavatica, our pipeline starts by building the heterogeneous network, generating Mango Graph Studio scripts to combine multiple networks, and enabling users to deduce the adoption trend of authors among multiple search terms. As an example, we used our Cavatica pipeline on the search results for the names of 9 different network analysis software tools, and identified the adoption trends among those tools.