In a complex and dynamic field, such as computer science, it is of interest to understand what software resources are available and the usage and purpose of these resources. We demonstrate the feasibility of automatically identifying resource names from scientific literature in arXiv’s database and show that the generated data can be used for exploration of software and topics. While scholarly literature surveys can provide some insights on what is being used by researchers, large-scale computer-based approaches to identify methods and technology from primary literature is needed to enable systematic cataloguing. Further, these approaches will facilitate the monitoring of usage in a more effective method. We developed a software tool using Natural Language Processing to determine if articles relate to the technology and methods of question. We then evaluated a trend of technology and methods used in each specific area of science. As we continue to expand this software, we will also analyze the researchers’ sentiment about the technology and methods to quantify funded research.
