Analysis of In text Citation Patterns in Local Journals for Ranking Scientific Documents

Abstract

In-text citations have been put forward as a new way to overcome the bias inherent in bibliographic citation analysis. In-text citation patterns have been used as the basis for citation analysis previously, but all the evidence has come from international journals. However, many countries have more local journals than international journals. This paper uses in-text citation analysis to examine local journals in Indonesia. The paper aims to determine the location-based citation pattern in the text and its effect on the articles’ and authors’ rankings. We collected articles from seven food science journals and then parsed these articles to detect the citations and their locations within the text. Pre-processing included normalizing section names, developing a database, and matching citation identities. The rankings were based on sections and then evaluated using the Spearman rank correlation in the final step. The results revealed that Indonesian journals did not exhibit the same patterns as international journals. There were differences in the section locations of the highest percentages of citations, the distributions of publication years, and the ranking methods. The correlations between sections indicated that the citations in the results and discussion section should be give the highest weight, followed by those in the method section, while the lowest weight should be assigned to citations in the introduction. These results need to be strengthened with further research using more extensive data and fields. Other findings, such as nonstandard and inconsistent citations, made developing an automatic citation detection system for local journals challenging.