How are social and intellectual relations structured and given shape within research universities? To answer these questions, we test to what extent various theoretically predicted processes explain the dynamics of academics’ networks of collaboration and shared language use in a unique longitudinal data set (1994 to 2005) of 2,631 faculty at a large private American university. Using the latest advances in stochastic actor-oriented models (in RSiena) and text analysis, we found that social and intellectual relations are clustered and centralized on bridging faculty who form a broader interdisciplinary hub of research in the university, and that, over time, this hub disseminated its style of (interdisciplinary) research to other faculty. These networks are shaped by selection based on age, gender, race, and academic rank as well as the coevolution of social and intellectual relations over time. Clear differences emerge in science, technology, engineering, and mathematics (STEM) fields and are strongly driven by structural mechanisms of clustering and centralization, whereas non-STEM fields (social sciences and humanities) are strongly driven by personal preferences of faculty members.

中文翻译：

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头脑会议：在大学内部建立社交网络和知识网络

研究型大学内部的社会和智力关系是如何构建和形成的？为了回答这些问题，我们测试了在多大的美国私立大学的2,631名教师的独特纵向数据集中（1994年至2005年），各种理论上预测的过程在多大程度上解释了学者合作和共享语言使用动态。利用随机行为者导向模型的最新进展（在RSiena中）和文本分析，我们发现社会和智力关系聚集并集中在桥接教师上，这些教师构成了大学更广泛的跨学科研究中心，并且随着时间的推移，该中心向其他教师传播了其（跨学科）研究风格。这些网络是根据年龄，性别，种族，以及学术排名，以及随着时间的流逝社会和知识关系的共同发展。在科学，技术，工程和数学（STEM）领域中出现了明显的差异，并且强烈地受到集群和集中化的结构机制的驱动，而对于非STEM领域（社会科学和人文科学）则强烈地由教师的个人偏好驱动。