Abstract
The aim of this literature review is to examine the current state-of-the-art in the area of citation classification. In particular, we investigate the approaches for characterising citations based on their semantic type. We conduct this literature review as a metaanalysis covering 60 scholarly articles in this domain. Although we included some of the manual pioneering works in this review, more emphasis is given on the later automated methods, which use Machine Learning and Natural Language Processing (NLP) for analysing the fine-grained linguistic features in the surrounding text of citations. The sections are organised based on the steps involved in the pipeline for citation classification. Specifically, we explore the existing classification schemes, datasets, pre-processing methods, the extraction of contextual and non-contextual features and the different types of classifiers and evaluation approaches. The review highlights the importance of identifying the citation types for research evaluation, the challenges faced by the researchers in the process and the existing research gaps in this field.