Connectivity in a citation network: The development of DNA theory☆

Abstract The study of citation networks for both articles and journals is routine. In general, these analyses proceed by considering the similarity of articles or journals and submitting the set of similarity measures to some clustering or scaling procedure. Two common methods are found in bibliometric coupling, where two citing articles are similar to the extent they cite the same literature, and co-citation analysis where cited articles are similar to the extent they are cited by the same citing articles. Methods based on structural and regular equivalence also seek to partition the article based on their positional location. Such methods have in common focus on the articles and partitions of them. We propose a quite different approach where the connective threads through a network are preserved and the focus is on the links in the network rather than on the nodes. Variants of the depth first search algorithm are used to detect and represent the mainstream of the literature of a clearly delineated area of scientific research. The specific citation network is one that consists of ties among the key events and papers that lead to the discovery and modeling of DNA together with the final experimental confirmation of its representation.

[1]  L. Freeman.  Centrality in social networks conceptual clarification , 1978 .

[2]  I ASIMOV.  THE GENETIC CODE. , 1965, New York state journal of medicine.

[3]  Francis Narin,et al.  Clustering of scientific journals , 1973, J. Am. Soc. Inf. Sci..

[4]  H. White,et al.  “Structural Equivalence of Individuals in Social Networks” , 2022, The SAGE Encyclopedia of Research Design.

[5]  Patrick Doreian,et al.  Structural equivalence in a psychology journal network , 1985, J. Am. Soc. Inf. Sci..

[6]  D J PRICE,et al.  NETWORKS OF SCIENTIFIC PAPERS. , 1965, Science.

[7]  B. C. Griffith,et al.  The Structure of Scientific Literatures I: Identifying and Graphing Specialties , 1974 .

[8]  H. Small.  A Co-Citation Model of a Scientific Specialty: A Longitudinal Study of Collagen Research , 1977 .

[9]  P. Arabie,et al.  An algorithm for clustering relational data with applications to social network analysis and comparison with multidimensional scaling , 1975 .

[10]  Eugene Garfield,et al.  THE USE OF CITATION DATA IN WRITING THE HISTORY OF SCIENCE , 1964 .

[11]  B. C. Griffith,et al.  The Structure of Scientific Literatures II: Toward a Macro- and Microstructure for Science , 1974 .

[12]  M. Callon,et al.  From translations to problematic networks: An introduction to co-word analysis , 1983 .

[13]  K. Reitz,et al.  Graph and Semigroup Homomorphisms on Networks of Relations , 1983 .

[14]  Francis Narin,et al.  Interrelationships of scientific journals , 1972, J. Am. Soc. Inf. Sci..

[15]  John N. Warfield,et al.  Combinatorial Connectivities in Social Systems , 1979, IEEE Transactions on Systems, Man, and Cybernetics.

[16]  Patrick Doreian,et al.  Structural equivalence in a journal network , 1985, J. Am. Soc. Inf. Sci..

[17]  Timothy Lenoir.  Quantitative Foundations for the Sociology of Science: On Linking Blockmodeling with Co-Citation Analysis , 1979 .

[18]  Eugene Garfield,et al.  Citation indexing - its theory and application in science, technology, and humanities , 1979 .

[19]  E. Noma.  USING INFLUENCE WEIGHTS TO EVALUATE THE SCIENTIFIC IMPORTANCE OF JOURNALS , 1988 .

[20]  Gabriel Pinski,et al.  Citation influence for journal aggregates of scientific publications: Theory, with application to the literature of physics , 1976, Inf. Process. Manag..

[21]  Ronald S. Burt,et al.  Positions in Networks , 1976 .

[22]  Henry G. Small,et al.  Co-citation in the scientific literature: A new measure of the relationship between two documents , 1973, J. Am. Soc. Inf. Sci..

[23]  M. M. Kessler.  Bibliographic coupling between scientific papers , 1963 .

[24]  R. Brieger.  Career Attributes and Network Structure: A Blockmodel Study of a Biomedical Research Specialty , 1976 .