My name is Irina Agoulnik and I am the 2011 Program Chair of the Social Network Analysis (SNA) TIG. My day-to-day job involves management of a large Interdisciplinary Research Consortium (IRC) funded by the National Institutes of Health (NIH) Common Fund. To assess the effect that interdisciplinary approaches might have on scientific productivity and innovation in biomedical research, we performed a local evaluation of the IRC. We incorporated SNA into the evaluation to visualize the development of collaborations across multiple sites and to learn about the integration between three distinct disciplines within our IRC.
Hot Tip #1: While planning a survey-based SNA evaluation of the scientific team network, we took into consideration two factors: the size of the observed network and its stability during the evaluation period. Regular shifts in personnel due to new appointments, career growth, and postdoctoral training affect the consistency of the network over time. On the other hand, representation of the network is incomplete, and network metrics potentially inconclusive, when only the steady group of collaborative Principal Investigators is taken into account. By merging the data from postdoctoral fellows and Principal Investigators into one network, we were able to make annual observations about the expansion of collaborations and to detect cross talk between the IRC disciplines.
Hot Tip #2: SNA can be used as a monitoring (rather than evaluation) tool for a large research consortium. By creating annual snapshots of the team science network and visualizing major integration hubs and their origins, the consortium management can observe changes in the ongoing complex research network (multi-site, multi-discipline) and make timely resource adjustments.
Hot Tip #3: Interdisciplinary team science network visualization and analysis based on bibliometric data (journals, co-authorship, citations, etc.) is a powerful approach to evaluation of scientific productivity and collaboration. However, this approach is best applied to a program with over three years of collaborative team science history so that there is time for collaborative scholarship to develop and for manuscripts to be published.
Rad Resources: The following software packages were designed specifically for SNA or have components that are useful for SNA:
- UCINET is an SNA program developed by Steve Borgatti, Martin Everett and Lin Freeman and distributed by Analytic Technologies: http://www.analytictech.com/ucinet/
- Pajek is a software program for large networks and for visualization: http://pajek.imfm.si/doku.php
- The R Project has software packages specifically for SNA: http://www.R-Project.org
The American Evaluation Association is celebrating SNA TIG Week with our colleagues in the Social Network Analysis AEA Topical Interest Group. The contributions all this week to aea365 come from our SNA TIG members and you can learn more about their work via the SNA TIG sessions at AEA’s annual conference. Do you have questions, concerns, kudos, or content to extend this aea365 contribution? Please add them in the comments section for this post on the aea365 webpage so that we may enrich our community of practice. aea365 is sponsored by the American Evaluation Association and provides a Tip-a-Day by and for evaluators.