Linking Behavior in the PER Coauthorship Network

Authors : Katharine A. Anderson, Matthew Crespi, Eleanor C. Sayre

There is considerable long-term interest in understanding the dynamics of collaboration networks, and how these networks form and evolve over time. Most of the work done on the dynamics of social networks focuses on well-established communities.

Work examining emerging social networks is rarer, simply because data is difficult to obtain in real time. In this paper, we use thirty years of data from an emerging scientific community to look at that crucial early stage in the development of a social network.

We show that when the field is very young, islands of individual researchers labored in relative isolation, and the co authorship network is disconnected. Thirty years later, rather than a cluster of individuals, we find a true collaborative community, bound together by a robust collaboration network.

However, this change did not take place gradually — the network remained a loose assortment of isolated individuals until the mid-2000s, when those smaller parts suddenly knit themselves together into a single whole.

In the rest of this paper, we consider the role of three factors in these observed structural changes: growth, changes in social norms, and the introduction of institutions such as field-specific conferences and journals.

We have data from the very earliest years of the field, and thus are able to observe the introduction of two different institutions: the first field-specific conference, and the first field-specific journals.

We also identify two relevant behavioral shifts: a discrete increase in co authorship coincident with the first conference, and a shift among established authors away from collaborating with outsiders, towards collaborating with each other. The interaction of these factors gives us insight into the formation of collaboration networks more broadly.


Coauthorship networks: A directed network approach considering the order and number of coauthors

« In many scientific fields, the order of coauthors on a paper conveys information about each individual’s contribution to a piece of joint work. We argue that in prior network analyses of coauthorship networks, the information on ordering has been insufficiently considered because ties between authors are typically symmetrized. This is basically the same as assuming that each co-author has contributed equally to a paper. We introduce a solution to this problem by adopting a coauthorship credit allocation model proposed by Kim and Diesner (2014), which in its core conceptualizes co-authoring as a directed, weighted, and self-looped network. We test and validate our application of the adopted framework based on a sample data of 861 authors who have published in the journal Psychometrika. Results suggest that this novel sociometric approach can complement traditional measures based on undirected networks and expand insights into coauthoring patterns such as the hierarchy of collaboration among scholars. As another form of validation, we also show how our approach accurately detects prominent scholars in the Psychometric Society affiliated with the journal. »