This project aims to develop methods of tracking how concepts emerge, are disseminated, stabilize and decay across different disciplines and through time. The goal to characterize and predict the emergence of concepts in active areas of research and to qualify the optimal conditions for producing innovative and generative concepts. The fundamental questions this project seeks to answer are…

• What is typically involved in creating, defining and presenting new concepts?
• How do concepts’ acceptance and use relate to the environment in which it was created and defined?
• Are there commonalities in the lives of concepts across disciplines?
• Are there properties, intrinsic or extrinsic, that might predict the longevity or generative capacity of a topic?
• How are some concepts borrowed and reapplied across fields?
• And what properties might predict the way a concept decays?

By using existing tools and techniques in NLP, machine learning and network science, as well as developing new ones, this project will help automate a number of quantitative and qualitative tasks related to scholarly research and knowledge creation:

• Identifying particularly productive and innovative fields.
• Comparing how conditions such as funding, organization and staffing of research institutions, affect the lives of concepts.
• Identifying particularly influential fields, institutions and researchers.
• Understanding how, when and why some concepts “stick” while many fade away.

In each situation, the analysis of a concept relies centrally on making sense of changing relationships. The time-wise examination of concepts having a “life” or a “path”, will lend to the predictive aspects of concept analysis. Additionally, it may yield insights into how research in different disciplines can be made sustainably productive.