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Understanding Interdisciplinary Collaborations as Social Networks

机译:将跨学科的合作理解为社交网络

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The dynamics of interdisciplinary collaboration invite further investigation if we are to make this endeavour more rewarding and productive. We are using social network analysis to track the development of a new interdisciplinary collaboration on complex interventions to improve population health. It involves nineteen scholars across four countries. We report the Baseline network of formal relationships among the scholars, along with the impact of the collaboration on these relationships in the first 18 months. We observed statistically significant increases in the density of six types of relationship networks: citing publications by other members of the collaboration, email contact, meeting with each other (outside of the formal annual meeting), visiting one another's institution, submitting research grants together and working on research projects together. The initial strategic role in the network of key 'gate keepers' has not altered substantially (betweenness centralization of the networks), but reciprocity has increased, that is, people are more likely to cite those who have cited them and work together. Increased collaboration is also reflected in the rise in number of subgroups over time and the increase in the average number of subgroup memberships. Use of social network analysis to understand the dynamics of interdisciplinary collaborations is a relatively new field. It invites reflection about what the optimal network structures for interdisciplinary collaborations would look like.
机译:如果我们要使这项工作更加有意义和富有成效,那么跨学科合作的动力就需要进一步研究。我们正在使用社交网络分析来跟踪关于复杂干预措施以改善人口健康的新的跨学科合作的发展。它涉及四个国家的19名学者。我们报告了学者之间正式关系的基准网络,以及前18个月合作对这些关系的影响。我们观察到六种类型的关系网络的密度在统计上显着增加:引用了其他协作成员的出版物,通过电子邮件联系,彼此开会(在正式的年会之外),访问彼此的机构,一起提交研究资助以及一起研究项目。关键“守门人”网络中最初的战略角色并未发生实质性变化(网络之间的中间集中),但互惠性却有所提高,也就是说,人们更容易引用那些引用他们并共同努力的人。随着时间的推移,子组数量的增加和子组成员的平均数量的增加也反映了协作的增强。使用社交网络分析来了解跨学科合作的动态是一个相对较新的领域。它引起人们对跨学科协作的最佳网络结构的外观的思考。

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