A Novel Approach to Citation Normalization: A Similarity-Based Method for Creating Reference Sets

A similarity-oriented approach for deriving reference values used in citation normalization is explored and contrasted with the dominant approach of utilizing database-defined journal sets as a basis for deriving such values. In the similarity-oriented approach, an assessed article's raw citation count is compared with a reference value that is derived from a reference set, which is constructed in such a way that articles in this set are estimated to address a subject matter similar to that of the assessed article. This estimation is based on second-order similarity and utilizes a combination of 2 feature sets: bibliographic references and technical terminology. The contribution of an article in a given reference set to the reference value is dependent on its degree of similarity to the assessed article. It is shown that reference values calculated by the similarity-oriented approach are considerably better at predicting the assessed articles' citation count compared to the reference values given by the journal-set approach, thus significantly reducing the variability in the observed citation distribution that stems from the variability in the articles' addressed subject matter.