Abstract(s)
Using the full-text corpus of more than 75,000 research articles published by seven PLOS journals, this paper
proposes a natural language processing approach for identifying the function of citations. Citation contexts are
assigned based on the frequency of n-gram co-occurrences located near the citations. Results show that the most
frequent linguistic patterns found in the citation contexts of papers vary according to their location in the IMRaD
structure of scientific articles. The presence of negative citations is also dependent on this structure. This
methodology offers new perspectives to locate these discursive forms according to the rhetorical structure of
scientific articles, and will lead to a better understanding of the use of citations in scientific articles.