[ Back to EurekAlert! ] Public release date: 12-Sep-2012
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Contact: A'ndrea Elyse Messer
aem1@psu.edu
814-865-9481
Penn State

NSF grant supports innovative big data social science training

An interdisciplinary team of Penn State researchers is creating a new training program for doctoral students in Big Data Social Science, with the help of a National Science Foundation grant totaling $3 million over five years.

The competitive grant is coordinated through the NSF Integrative Graduate Education and Research Traineeship (IGERT) program. This is only the second IGERT grant awarded to Penn State over the past decade.

"Every day, millions of new human interactions are recorded and millions of old human interactions are digitized, creating massive new sources of data about cooperation, conflict and every social behavior in between," said Burt Monroe, associate professor of political science and director of the Big Data Social Science project at Penn State. "There is a great opportunity here, but no single scientific discipline has all of the tools necessary to meet the challenges."

The Penn State team is developing a new curriculum and degrees in social data analytics, bringing together the social, statistical, computational and visual sciences, aiming to help create an innovative new generation of scientists equipped to address the scientific, economic, social and ethical challenges of massive and complex socially generated data.

Susan Welch, dean of the College of the Liberal Arts, said, "Since its founding, Penn State has been a national leader in interdisciplinary research and teaching by expanding the frontiers of knowledge and contributing to the enrichment of society. The Big Data Social Science project is among the newest initiatives to train future teachers and scientists who will lead the way in the advanced technologies of data science and analytics."

The NSF IGERT program aims to establish new models of graduate education by training young doctoral scientists and engineers in a collaborative research environment transcending traditional disciplines. Each of the five years, several two-year traineeships of $30,000 each will be awarded to doctoral students drawn from across the University in the social sciences -- including political science, sociology, criminal justice, demography, human development, health policy, anthropology, economics and communications -- geography, computer science, information science and statistics.

The trainees will engage in multidisciplinary classwork and research experiences in social data analytics including machine learning, statistics, visual analytics, social science methodology and the ethics and scientific responsibility of big social data. They will be able to take part in research rotations in various Penn State labs and projects involving big social data. Summer research externships will be available with corporate, government and nonprofit partners. The project also will host challenge competitions, hackathons and collaborative research activities.

Among the research team members are Monroe, principal investigator and director of the Quantitative Social Science Initiative; associate director Christopher Zorn, research professor of political science; and co-principal investigators C. Lee Giles, the David Reese Professor in Information Sciences and Technology and professor of computer science and engineering; Melissa Hardy, Distinguished Professor of Sociology and Demography; Alan MacEachren, professor of geography and director of the GeoVISTA Center; and Aleksandra Slavkovic, associate professor of statistics and public health sciences.

Seven Penn State doctoral students have been named to the first cohort of Big Data Social Science IGERT Trainees: Beatrice Abiero, health policy and demography; Margaret Ariotti, political science; Muhammed Idris, political science; Joshua Stevens, geography; Jennifer Smith, geography; Stephanie Wilson, human development and family studies; and Mo Yu, information sciences and technology.

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More information can be found at http://bdss.psu.edu.



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