Social Networking in an Agricultural Research Center: Using Data to Enhance Outcomes

ABSTRACT The purpose of this article is to present a case study of one midwestern Agricultural Center (Ag Center) that used social network analysis (SNA) to (1) evaluate its collaborations with extramural stakeholders and (2) strategically plan for extending outreach for goal achievement. An evaluation team developed a data collection instrument based on SNA principles. It was administered to the Ag Center’s intramural stakeholders (N = 9), who were asked to identify the key extramural stakeholders with whom they had collaborated within the previous 12 months. Additional questions about each extramural stakeholder helped to categorize them according to SNA network measures for degree of centrality, betweenness centrality, and closeness centrality. Findings showed the Ag Center had N = 305 extramural stakeholders. Most of these were other researchers and did not represent the diverse group of stakeholders that the Ag Center had targeted for engagement. Only a few of the intramural stakeholders had national or international connections. Findings were used to improve and diversify connections in order to leverage the Ag Center’s expertise and ability to translate research into new best practices and policies. The SNA case study has implications for other evaluators and project directors looking for methodologies that can monitor networks in large science consortia and help leaders plan for translating research into practice and policies by networking with those who can influence such change.

[1]  Lauren M. Menger,et al.  Strengthening suicide prevention networks: Interorganizational collaboration and tie strength , 2015 .

[2]  Michael E Hughes,et al.  Network Dynamics to Evaluate Performance of an Academic Institution , 2010, Science Translational Medicine.

[3]  Raffaele Vacca,et al.  Designing a CTSA‐Based Social Network Intervention to Foster Cross‐Disciplinary Team Science , 2015, Clinical and translational science.

[4]  M. Cramer,et al.  Measuring community coalition effectiveness using the ICE instrument. , 2006, Public health nursing.

[5]  R. Rimal,et al.  Why health communication is important in public health. , 2009, Bulletin of the World Health Organization.

[6]  Erika E Scott,et al.  Building Safety Partnerships Using Social Network Analysis , 2013 .

[7]  D. Blumenthal,et al.  Measuring Vital Signs: an IOM report on core metrics for health and health care progress. , 2015, JAMA.

[8]  Shalin Hai-Jew Analyzing Social Media Networks with NodeXL: Insights from a Connected World , 2012 .

[9]  Thomas W. Valente,et al.  Social Networks and Health , 2010 .

[10]  Jenine K. Harris,et al.  Network Influences on Dissemination of Evidence-Based Guidelines in State Tobacco Control Programs , 2013, Health education & behavior : the official publication of the Society for Public Health Education.

[11]  Harold Alan Pincus,et al.  Evaluation and the NIH Clinical and Translational Science Awards , 2013, Evaluation & the health professions.

[12]  M. Petrescu-Prahova,et al.  Using Social Network Analysis to Assess Mentorship and Collaboration in a Public Health Network , 2015, Preventing chronic disease.

[13]  Stanley W. Borg Social Networks and Health: Models, Methods, and Applications , 2012 .

[14]  Walter W. Powell,et al.  Knowledge Networks as Channels and Conduits: The Effects of Spillovers in the Boston Biotechnology Community , 2004, Organ. Sci..

[15]  Geoff Kaine,et al.  Agricultural Knowledge and Information Systems: A Network Analysis , 1999 .

[16]  Exploring the role of communications in quality improvement: A case study of the 1000 Lives Campaign in NHS Wales , 2015, Journal of communication in healthcare.

[17]  Radhakrishnan Nagarajan,et al.  Social Network Analysis to Assess the Impact of the CTSA on Biomedical Research Grant Collaboration , 2015, Clinical and translational science.

[18]  Lei Wang,et al.  The Quantitative Evaluation of the Clinical and Translational Science Awards (CTSA) Program Based on Science Mapping and Scientometric Analysis , 2013, Clinical and translational science.

[19]  Matthew Semadeni,et al.  Value of Strong Ties to Disconnected Others: Examining Knowledge Creation in Biomedicine , 2009, Organ. Sci..