EAGER: Identifying and Capitalizing on Schools of Thought as a Basis for Virtual Communities in Computer Science and Engineering Research

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As the computer science and engineering research community continues its unbroken half-century streak of exponential growth, the community's old ways of finding community and collaboration are falling apart. Research results are generated and shared at a much faster rate than in the past, but relationship-building opportunities are lower than ever – and human relationships are an essential component of the research enterprise. Already data-oriented research conferences have grown too large to be effective for many of their original purposes, such as fostering community and shared purpose; meeting new potential peer collaborators and building relationships with them in person; providing an opportunity for junior researchers to connect to senior researchers and build the loose ties that are so important for careers; and providing an occasion to not only learn about the latest research results (which are now instantly available on the internet) but also to interact with the researchers who produced those results and probe beyond the surface of publications. COVID-19 is accelerating that trend. Most conferences have chosen to become virtual, which makes them more accessible to all, often at no cost; but the chance to interact one-on-one is greatly reduced or even absent, as are networking opportunities and community-building. To address these problems, this exploratory data science project will analyze the extensive data available about existing research collaborations and create methods to identify specific potential new relationships and collaborations that have the potential to enhance the pace and trustworthiness of scientific innovation, while encouraging cross-fertilization of ideas, methods, and techniques. As an integral part of the project, the investigator will train two undergraduates in data science.Drawing on techniques from social network community detection and characterization, recommender systems, and social network visualization, the project will produce new methods to identify and characterize existing small close-knit research communities, or "schools of thought" based on publicly available information about collaborations and other relationships between researchers. The project will propose methods to bring together complementary schools of thought, based on an analysis of the characterization of past highly successful collaborations. The resulting new virtual communities will still be small enough for extensive one-on-one interaction, which will support both the promotion of existing bonds and the formation of new ones. The project's methods will be pilot tested at a major computer science conference, and the project's code will be made publicly available.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.