Hybrid Model for Conducting Multiple Citation Analysis Operations Using the Same Citation Data

Abstract

This study proposes a hybrid model, which can be used for conducting various citation analysis operations over a set of research works/papers interconnected with each other through their citations and references. Citation analysis of papers becomes important while evaluating their role and influence in a particular field and understanding their relation and connectivity of content with other important documents in the same field. The citation analysis methods can further be used for tracing the relationship between domains, keywords, and many other relative factors, based on the criteria considered for citation analysis operation. The research in the field of citation analysis, traditionally focussed on developing new citation analysis methods for better evaluation or ranking of the papers. This paper proposes a model, where multiple existing citation analysis operations can be implemented in a single platform. The proposed model calculates the result for co-citation analysis, bibliographic coupling, and citation density analysis. The process involved in the development of this model is discussed in detail in the later part of the manuscript. The process is based on computational coding, and hence special attention needs to be paid to the proper arrangement of papers in tabular form, based on the information of their year of publication and their citation network data. An algorithm for the model has been proposed in the later part of the manuscript that is based on the code formulated to find the relative data for conducting the operations.