EAGER: Collaborative Research: FLASH! Fueling Learning Alliance in Sustainability in Higher education: Using social media and networks for science

虽然有相当多的证据表明，社交媒体的效用使分散和多样化的科学界之间能够进行高水平的合作和交流，但很少有实证证据表明，社交媒体的效用可以帮助个人在这些社区中找到合适的人进行联系。与合适的人建立联系在创造大规模创新和接受全球问题方面尤其具有催化作用，例如超越地理、文化和学科的可持续发展。我们建议将从NSF Voss项目中获得的见解应用于NSF Voss项目(在西北大学)，调查是什么促使在虚拟组织中形成有效的网络，以加强NSF Sees项目(以科罗拉多州立大学为依托)发展全球女性学者网络(GWSN)的指导实践。我们的目标是实施和评估社会推荐系统的利用和成果，该系统将寻求在全球范围的可持续发展知识网络中加强对基层妇女与学者、政策领导人和学生的交叉指导。我们在测试社交网络推荐系统是解决与可持续发展相关的科学和政策决策方面挥之不去的男女差距的有效方式这一假设方面迈出了冒险的一步。我们假设，社交推荐系统创建了一个跨越文化、地理和机构差距(草根到学术、女性到学生、政策制定者到研究生)的知识网络云。这样的云网络是一种可以对科学的传播方式和参与交流的人产生革命性变化的方式。

While there has been considerable evidence of the utility of social media to enable high levels of collaboration and communication among distributed and diverse scientific communities, there is very little empirical evidence about the utility of social media to help individuals find the right people to connect with in these communities. Connecting with the right individuals is particularly catalytic in creating large scale innovation and acceptance of global issues such as sustainable development which transcends geography, culture and disciplines. We propose to apply the insights gained from an NSF VOSS project (at Northwestern University) investigating what motivates the formation of effective networks in virtual organizations to enhance mentoring practices in the NSF SEES project (anchored at Colorado State University) developing the Global Women Scholars Network (GWSN). Our goal is to implement and evaluate the utilization and outcome of a social recommender system that will seek to enhance cross-mentoring of grassroots women with academics, policy leaders and students in the globally-scaled knowledge network for sustainability. We take a risky step in testing the hypothesIs that social network recommender systems are an effective way to address the lingering gap between women and men in the sciences and policy decision-making associated with sustainable development. We posit that social recommender systems create a knowledge network cloud that merges across cultural, geographic, and institutional gaps (grassroots to academic, women to students, and policy makers to graduate students). Such a cloud network is one way that can make a transformational change in how science is communicated and who is engaged in that communication.