Let’s take a closer look at the scholars behind the publications. For that purpose, I’ve inverted the network from the last post . Now, vertices represent authors and a tie indicates a journal, in which both authors have published. The ties are stronger if both authors wrote several articles for the same journals. The size of a node represents the number of articles in our database from that particular author.
Again, we can identify our four clusters:1) Upper left: sociological studies 2) Upper right: organization and management studies 3) Lower left: research on higher education management and 4) Lower right: studies on technology transfer and science communication.
Now, a high betweenness centrality of an author indicates boundary spanning research by contributing to journals in different discourses. The authors with the highest betweenness are: 1 Cynthia Hardy (1350), 2 Loet Leydesdorff (723), 3 Ase Gornitzka (643), 4 Georg Krücken (627) and 5 Karl Weick (610). If an author has a high degree centrality (i.e. the node has many direct ties) he or she is well connected in terms of journal diversity. In contrast to the betweenness measure, diversity in this case most likely refers to journal diversity within a certain discourse. The top five authors according to degree centrality are: 1 Barbara Sporn (27), 2 Royston Greenwood (26), 3 Georg Krücken (24), 4 Dennis Gioia (22), 5 Christopher Hinnings (22).
Of course, the shown results are limited in terms of generalizability. The measures reflect only a part of the authors’ works and should not be interpreted as an indicator for performance. Besides, the network is only based on 68.6% (more like 40%, since I’ve removed quite some isolates) of all the publications that happend to find their way into our database, which, obviously, is pre-selected by subjective preferences for specific theories, contexts, and methods. However, the networks provide useful information about the foundations of our work at a glance. I wonder how the actual collaboration network looks like..