Diversity measures and network centralities as indicators of interdisciplinarity: case studies in bionanoscience

• http://dimetic.dime-eu.org/dimetic_files/phd_2007-1_RAFOLS.pdf
• Ismael Rafols and Martin Meyer

However, as outlined above, there are several reasons for avoiding categorisation. In the first place, the only multidisciplinary and most widely used categorisation system is the one provided by ISI, which assigns each journal to one or more disciplines. This may work at the journal level, but is very problematic at the paper level given the heterogeneous contents of many journals.

About the issue with bibliographic coupling (which can be addressed by Continuous embedding or Representation learning):

This measure has a notable downside: if two papers do not share any reference, their similarity is set to 0, irrespectively of their location in the wider context provided. In other words: if they don’t share a reference, the distance between a paper in biophysics and one in biochemistry is assumed to be the same as between one in biophysics and one in sociology.