UFII Covid Seed Awardees Virtual Seminar Series – Drs. Vacca & Tang
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UFII Covid Seed Awardees Virtual Seminar Series – Drs. Vacca & Tang
December 11, 2020 @ 12:00 pm - 1:30 pm
UFII COVID-19 SEED Awardees Virtual Seminar Series
“Covid-19, an accelerator of science: Evidence from convergence in collaboration and language”
by Dr. Raffaele Vacca, Assistant Professor in the Department of Sociology and Criminology & Law, and Dr. Kevin Tang, Assistant Professor in the Department of Linguistics
Co-authors: Till Krenz, Post-doctoral Research, Network Science Program, CTSI, and UFII Fellow, and Thomas Smith, doctoral candidate, Department of Sociology and Criminology & Law
Friday, December 11, 2020
12:00PM – 1:00PM
ABSTRACT:
How do science and scientific collaboration respond to global health crises? Do these crises reinforce, accelerate or disrupt normal trends in the production of science? This project analyzes CORD-19, a growing dataset of over 200,000 scientific articles published about coronavirus/Covid-19 over the years, and Dimensions, a global bibliographic database, to study the impacts of Covid-19 on global trends in scientific production and collaboration. Drawing on theories and methods from sociolinguistics, natural language processing, and network science, we hypothesize that the Covid-19 pandemic has operated as an accelerator of long-term trends in science, including the growth in collaboration, interdisciplinarity, and cross-domain cooperation (e.g., between academic and health care institutions). We examine different types of scientific convergence produced by Covid-19, including convergence in collaboration between different disciplines, institutions, institutional domains, and countries; and convergence in terms of topics addressed and language used in coronavirus literature over time. We consider the effects of both the 2002-2004 SARS epidemic and the current pandemic, comparing collaboration and convergence patterns pre, during and post each of these two global health crises.
Bios:
Dr. Raffaele Vacca is an assistant professor in the UF Department of Sociology and Criminology & Law, and co-director of the Network Science Program in the UF Clinical and Translational Science Institute. A sociologist by background, he conducts research on social networks, international migration, and the sociology of science. His most recent work focuses on methods for personal network analysis and on how social relationships influence individual and group outcomes in a variety of domains, such as immigrant incorporation, health disparities, and scientific production. Website: http://www.raffaelevacca.com/
Dr. Kevin Tang is an assistant professor in Computational Language Science at the UF Department of Linguistics. He is a co-director of the Speech, Lexicon and Modeling lab (SLaM lab, https://slam.lin.ufl.edu) and is currently a co-PI on NSF Award #2037266: SenSE: Smart Electropalatography for Linguistic and Medical Applications (SELMA). With a background in linguistics and engineering, Dr. Tang focuses on the intersections of laboratory phonology, computational linguistics, and psycholinguistics. Building on the techniques in natural language processing, he conducts research with real-world applications such as speech recognition systems for motor speech disorders, disfluency diagnostic toolkits, and language documentation of minority languages, Website: https://slam.lin.ufl.edu/people/kevin-tang/
Dr. Dr. Till Krenz earned his PhD in sociology at the University of Magdeburg in Germany. His work is focused on ego-centered network analysis, methods of the social sciences and statistical programming. He is the maintainer of egor, an R-Package for ego-centered network analysis. Krenz is working as a Post-Doc Researcher in the Network Science Program of the UF CTSI. His most recent work is on the analysis of the evolution of multiplex collaborative research networks and the application of Natural Language Processing techniques to better understand, describe and sculpt collaborative processes in academia.
Thomas Smith is a doctoral candidate in Sociology and Criminology & Law at the University of Florida, and an incoming postdoctoral researcher in the Network Science Program of the University of Florida’s Clinical and Translational Science Institute. Thomas’ research leverages network science, natural language processing, and machine learning to examine the biosocial relationship between networks of social support and criminal behavior, and the structural and dyadic predictors of scientific collaboration. His recent work has focused on assessing the impact of law enforcement crackdowns on co-offending networks and describing the curvilinear relationship between topic overlap and scientific collaboration.