Collaborative Research: Social Networking Tools to Enable Collaboration in the Tobacco Surveillance, Epidemiology, and Evaluation Network (TSEEN)

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A highly publicized report by the American Cancer Society noted that cancer has surpassed heart disease to become the number one killer of adults under the age of 85 in the United States today. At the top of the list was lung cancer, a disease that is eminently preventable. Addressing public health threats like cancer are acute, system-wide challenges that would benefit from network-centric approaches. For example, when the tobacco research community realized it had taken over a decade to discover that they had already collected substantial empirical evidence, distributed across its network of tobacco researchers, indicating that 'light' (low-tar/low-nicotine brands) cigarettes reduced neither exposure to nor risk of cancer, researchers began to understand the importance of effectively sharing resources and information across the entire community. In response, government agencies involved in public health have made a substantial foundational investment in developing a digital government cyberinfrastructure--Tobacco Systems integration Grid (TobacSIG)--to enable collaboration within the Tobacco Surveillance, Epidemiology, and Evaluation Network (TSEEN). While such an underlying cyberinfrastructure is a prerequisite, delays in discoveries (such as the carcinogenic effects of 'light' cigarette mentioned above) have prompted the TSEEN community to underscore the need for social network referral tools as a crucial component of any effort to enhance the efficacy of their collaboration system.This project will develop, deploy and assess social networking tools to enhance collaboration among members of TSEEN using the TobacSIG cyberinfrastructure. The proposed project brings together researchers in information science, social science, and public health who have established strong collaborations with government partners on the development of networks to support transdisciplinary research in public health. The researchers have assisted the government partners in formulating the challenges and envisioning solutions; hence the research team is will positioned to leverage the substantial financial and human resources being invested by NIH National Cancer Institute and its partner government agencies in the TobacSIG cyberinfrastructure.Intellectual Merit: The proposed project is a pioneering effort at incorporating social network referral tools as an integral part of collaborative systems within the context of digital government. First, the proposed project will extend theoretical understanding of the emergence of collaboration network structures involving multidimensional networks, where nodes may be individuals, documents, data sets, services (such as visual-analytic tools), or keywords/concepts. Second, it will pioneer theory development and testing about the influence of network referral systems on collaboration outcomes. Specifically, the proposed project will assess the extent to which collaboration outcomes are influenced by (i) different theoretically-derived structures of network referrals, (ii) different incentive structures provided to users of the network referral system, (iii) different types of network data used to generate referrals, and (iv) different information visualizations used to represent network referrals. Third, the research will extend the exponential random graph modeling techniques that have been largely used to estimate structural dependencies in relatively small (typically no larger than 500) one-dimensional networks. The proposed project will extend these techniques to multidimensional networks containing over 10,000 nodes.Broader Impacts: As cyberinfrastructure is deployed to support collaboration among large communities in government and elsewhere, it is increasingly obvious that social network tools have immense potential. In this project the researchers will seek to respond to the refrain 'if only the Tobacco Surveillance Epidemiology Evaluation Network knew what it knew.' Generalizing the relevance of this same refrain to a wide spectrum of other contexts is suggestive of the broader impacts of the proposed research. The findings and deliverables of the proposed research will be immediately generalizable to the design and deployment of social network referral tools to support collaboration among other digital government efforts within public health and beyond. Further, the government and non-government partners in this project are exceptionally well-equipped to incorporate into their regularly scheduled education, training, and outreach workshops the skill sets of collaborative fluency afforded by the judicious use of network referral systems. Finally, by definition, social network referral systems have the potential to increase the likelihood of drawing in more diverse constituents within the public health community (in terms of gender, ethnicity, age, seniority, disciplinary perspectives) than heretofore possible. This extended network will also offer opportunities for mentoring of previously disadvantaged members within these communities.