Full Professor, Colorado State University
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Data Analytics Laboratory


Collaboration and Social Networks

In this project, we are investigating the differnt analytical techniques and methodologies that might be appropriate to teams - their formation, collaboration and success. We focus on longitudinal analyses of the social networks formed by research collaborations at a Carnegie I research university. Over the last several years, many federal agencies, e.g., NSF, NIH, DOE, have recommended that funding proposals be submitted by collaborative interdisciplinary teams because of a growing acknowledgment of the importance of discoveries (and other outcomes) from interdisciplinary/multidisciplinary science and technology. This is based on theory that more weak-tie relationships will lead to an increase in innovation. By modeling, visualizing and analyzing these social networks, we compare and contrast funding relationships. We implement network measures of density, betweenness centrality, and eigenvectors and examine the rate of change in weak-tie and strong-tie social networks over time. We explore the strategic implications of structuring organizational responses to interdisciplinary collaboration.

Data

We use data from 3 different sources: publically available NSF and NIH award data, and an internal database of all funded research on campus. For example, within the NSF dataset, we downloaded and imported into SQL Server all 124,422 grants awarded by the NSF from 2001-2012 attributes including titles, abstracts, principal investigators, dates the award was active, as well as the institutions associated with the principle investigators. Separate entries of the same award are listed if funding is being sent to investigators that work for different institutions. Therefore, identifying collaborative awards was a process of searching for entries that had identical abstracts and multiple institutions. However, special care was given to identify instances of the same project having slightly different abstracts when listed for each institution (a small amount of data cleaning was required to merge these). For entries with no abstract, the project titles were manually examined and a decision was made about whether or not they were the same project. There are many NSF grants given for conference funding or other administrative endeavors, which were not included in analytics as our focus was on actual research related collaborative work.


NSF Force Atlas Visualization


NSF Force Atlas Visualization

Articles


Presentations


This research was supported by ISTEC at CSU, and Department of Computer Information Systems. Dr. Stephen C. Hayne - Principal Investigator
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