The structure and dynamics of cocitation clusters: A multiple‐perspective cocitation analysis

Abstract

A multiple-perspective co-citation analysis method is introduced for characterizing and interpreting the structure and dynamics of co-citation clusters. The method facilitates analytic and sense making tasks by integrating network visualization, spectral clustering, automatic cluster labeling, and text summarization. Co-citation networks are decomposed into co-citation clusters. The interpretation of these clusters is augmented by automatic cluster labeling and summarization. The method focuses on the interrelations between a co-citation cluster's members and their citers. The generic method is applied to a three-part analysis of the field of Information Science as defined by 12 journals published between 1996 and 2008: 1) a comparative author co-citation analysis (ACA), 2) a progressive ACA of a time series of co-citation networks, and 3) a progressive document co-citation analysis (DCA). Results show that the multipleperspective method increases the interpretability and accountability of both ACA and DCA networks.

Visualization of International Energy Policy Research

“…In order to gain a comprehensive and accurate understanding of the emerging scientific trends and to explore the structure and distribution of energy policy research, we have developed an analytical framework following the idea of Chen [11,12] (Figure 1). Selected articles and their citations (i.e., cited references) with a certain topic are retrieved from reliable and well-recognized databases (e.g., the WOS platform).…”

Visualization analysis of CRISPR/Cas9 gene editing technology studies

“…CiteSpace software adopts several structural metrics of co-citation networks, which include betweenness centrality, modularity, and silhouette (Chen et al, 2010). The betweenness centrality metric measures the extent of one node in the middle of a path that connects other nodes in the network (Brandes, 2001;Freeman, 1977).…”

“…These terms are sorted by term frequency-inverse document frequency (TF-IDF) algorithm, which is used to evaluate the importance of the word in an article. Labels selected by TF-IDF weightiness prefer to represent the most salient aspect of a cluster and emphasize the research mainstream (Chen et al, 2010).…”

Scientometric Analysis of the Researches About Technological Pedagogical Content Knowledge and Scholarly Communication

“…Bibliyografik veriler içerisindeki çalışmaların belli bir çalışmaya atıfta bulunması o çalışmanın içerikten bağımsız olarak incelenen veri seti içerisinde belli bir entelektüel değere sahip olduğu göstermektedir. Eser ortak atıf analizi sonucunda alanda meydana gelen değişimler ve yeni alt araştırma alanlarının oluşumu ve bu alanların gelişiminde etkileşim içinde bulundukları alanların belirlenmesi amaçlanmaktadır (Chen, Ibekwe-SanJuan ve Hou, 2010). Eser ortak atıf analizinde atıf sayılarına bağlı olarak alana yönelik bilişsel haritanın ortaya konulmasının yanı sıra alanda dönüm noktası oluşturabilecek değişimleri meydana getiren eserlerin istatistikî değerlere bağlı olarak ortaya konulmaktadır (Ramos-Rodríguez ve Ruíz-Navarro, 2004).…”