Mathieu O'Neil
Mathieu O’Neil is Professor of Communication in the News and Media Research Centre at the University of Canberra and Honorary Associate Professor of Sociology at the Australian National University. He researches issue diffusion, the political economy of digital commons and information resilience. He co-founded the ANU’s Virtual Observatory for the Study of Online Networks, a world leader in computational social science. He also founded and edited the peer-reviewed Journal of Peer Production (2011-2021) and founded an international think tank, the Digital Commons Policy Council [https://dcpc.info/]. Since 2022 he has led the co-design of media and information literacy resources for schools with ACT and NSW teachers and teacher-librarians [https://ucmethod.org/]. His research has been published in Social Networks; Information, Communication & Society; New Media and Society; Organization Studies; and the Journal of Quantitative Description: Social Media.
Session
Interdisciplinarity is commonly understood as the integration of knowledge from two or more distinct academic disciplines in scientific collaboration. Rather than treating interdisciplinarity solely as an outcome of knowledge integration, this study conceptualises it as the product of ongoing boundary negotiations among researchers from different disciplinary traditions (Gieryn, 1983). Existing studies predominantly assess interdisciplinarity at the level of publications, authors, journals, research fields, and formal organisational arrangements such as research centres, laboratories and grant scheme (Wang & Schneider, 2020). Less attention has been paid to cohesive collaborative communities formed through researchers’ informal collaborative ties, for example professional networks, conference interactions, and long-term interpersonal relationships, that may transcend organisational boundaries (Calvert, 2024). Examining such communities provides an opportunity to investigate how disciplinary boundaries are maintained, negotiated, or crossed within collaborative research.
Furthermore, existing interdisciplinary measures often implicitly assume that diversity scores are comparable across collaborations of different sizes (Porter & Rafols, 2009). However, group size constrains the maximum variety could be achieved, while group size and variety jointly constrain the range of possible diversity values. As a result, observed diversity should not be interpreted independently of the structural opportunities available to a collaboration. While existing measures quantify disciplinary diversity, they do not indicate whether a collaboration exhibits lower, expected, or higher diversity relative to its structural conditions. Consequently, they provide limited insight into whether diversity reflects structural characteristics of a collaboration, or active processes of disciplinary boundary maintenance and boundary crossing.
To address these gaps, we propose a framework that uses maximal clique as the unit of collaboration and residualised Shannon entropy as a measure of disciplinary boundary permeability. By modelling expected disciplinary diversity as a function of clique size and disciplinary variety, the framework evaluates interdisciplinarity relative to the structural opportunities available to each collaboration. This approach enables the identification of collaborative communities that exhibit higher or lower levels of boundary work than would be expected from their size and disciplinary composition. We subsequently classify maximal cliques into three types based on residualised Shannon entropy and interpret them through the lens of boundary work. Boundary-maintaining cliques have negative residual values, indicating lower observed diversity than expected.; boundary-neutral cliques have residual values close to zero, indicating diversity levels consistent with structural expectations; and boundary-crossing cliques have positive residual values, indicating higher observed diversity than expected.
To demonstrate the proposed framework, we constructed a coauthor network of 6,730 authors
from1,909 smart cities research articles published in 2022 indexed in Scopus. Maximal clique analysis identified 1,356 collaboration communities with at least 3 members. The overall residual diversity scores were negative (mean = -0.24, median = -0.49), with 58% of cliques were classified as boundary-maintaining (mean = -0.74), 24 % as boundary-neutral (mean = 0), and 18% as boundary-crossing (mean = 0.11). These findings suggest that while smart cities research is commonly characterised as interdisciplinary (Bibri, 2019), collaborations in this field largely maintained disciplinary boundaries with only a minority actively crossed disciplinary boundaries beyond what would be expected from their structural characteristics.
The proposed framework enables identification of informal collaborative communities that are observable only through co-author networks. It also disentangles structural opportunities from boundary work by distinguishing expected diversity from observed diversity. By doing so, it shifts attention from interdisciplinarity as an aggregated outcome to the ongoing processes through which disciplinary boundaries are maintained, negotiated, and crossed within collaborative communities.