Developing Guidelines for Reporting About Network Data

Michigan State University, East Lansing MI

Investigators

Abstract

This project facilitates the collaborative development of Guidelines for Reporting About Network Data (GRAND). Over the past decade, numerous studies of social networks have addressed key challenges in using networks to understand behavior. However, the rapid growth of network research has led to variation and inconsistency in reporting, which severely limits the understanding of network data and results. These guidelines enable network researchers to describe their network data clearly, consistently, and transparently and the project thereby enhances the value of existing network research in several ways. First, the guidelines create enhanced infrastructure for research and education by providing researchers, students, and journal peer reviewers with guidance on what to include when describing network data, or what to look for when reviewing research about network data. Second, the project encourages the full participation of women and underrepresented minorities in STEM by recruiting a demographically diverse working group to coordinate the development of guidelines and by disseminating guideline materials at no cost via publicly available repositories. Finally, the guidelines lead to increased public scientific literacy by providing a clear and concise way to describe network data, which helps the public better understand what network data are when they are described in media reports. Data-intensive methods such as meta-analysis have wide adoption of reporting protocols (e.g., PRISMA framework), but no similar guidance exists for research on networks. This project builds on the success of such widely adopted protocols, using the same collaborative guideline development process, to develop a similar set of guidelines for networks. Specifically, the process begins with recruitment of a working group, who survey the multi-disciplinary network research community. Preliminary guidelines are derived from the survey results at an initial conference, and are refined at a second conference using feedback from listening sessions. The final guidelines will be shared with network professional associations and network journals for their formal endorsement. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.