Is there really a Citation Age Bias in NLP?
Hoa Nguyen Steffen Eger
Citations are a key ingredient of scientific research to relate a paper to
others published in the community. Recently, it has been noted that there is a
citation age bias in the Natural Language Processing (NLP) community, one of
the currently fastest growing AI subfields, in that the mean age of the
bibliography of NLP papers has become ever younger in the last few years,
leading to `citation amnesia' in which older knowledge is increasingly
forgotten. In this work, we put such claims into perspective by analyzing the
bibliography of $\sim$300k papers across 15 different scientific fields
submitted to the popular preprint server Arxiv in the time period from 2013 to
2022. We find that all AI subfields (in particular: cs.AI, cs.CL, cs.CV, cs.LG)
have similar trends of citation amnesia, in which the age of the bibliography
has roughly halved in the last 10 years (from above 12 in 2013 to below 7 in
2022), on average. Rather than diagnosing this as a citation age bias in the
NLP community, we believe this pattern is an artefact of the dynamics of these
research fields, in which new knowledge is produced in ever shorter time
intervals.