Detecting Research Fronts Using Different Types of Combinational Citation

In this paper, we investigate the performance of different types of citation networks including different types of combinational citations for detecting emerging research fronts by a comparative study. In existing works, some types of citation network, such as direct-citation, co-citation and bibliographic coupling were tested in some research domains, separately. However, citation network with combinational types of citations, such as the citation network including directcitations and co-citations, have possibilities of finding the new research fronts. For detecting the research fronts, some types of citation networks were constructed for each research domain, and the papers in those domains were divided into clusters to detect the research front. In addition, we perform a comparative study to investigate the performance of some types of citation networks including combined ones for detecting emerging research field. Especially, we evaluate the performance of each type of weighted citation networks in detecting a research front by using the following measures of papers in the cluster: visibility, measured by normalized cluster size, speed, and topological relevance.

[1]  Ronald N. Kostoff,et al.  Database tomography for information retrieval , 1997, J. Inf. Sci..

[2]  Naoki Shibata,et al.  Comparative study on methods of detecting research fronts using different types of citation , 2009, J. Assoc. Inf. Sci. Technol..

[3]  Ismael Rafols,et al.  A global map of science based on the ISI subject categories , 2009, J. Assoc. Inf. Sci. Technol..

[4]  Henry Small.  Visualizing science by citation mapping , 1999 .

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

[6]  Kevin W. Boyack,et al.  Identifying a better measure of relatedness for mapping science , 2006 .

[7]  Bart Selman,et al.  Tracking evolving communities in large linked networks , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[8]  Henry G. Small,et al.  Tracking and predicting growth areas in science , 2006, Scientometrics.

[9]  Kevin W. Boyack,et al.  Mapping the backbone of science , 2004, Scientometrics.

[10]  Yoshiyuki Takeda,et al.  Detecting emerging research fronts based on topological measures in citation networks of scientific publications , 2008 .

[11]  Bruce Hendrickson,et al.  Knowledge Mining With VxInsight: Discovery Through Interaction , 1998, Journal of Intelligent Information Systems.

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

[13]  Kevin W. Boyack,et al.  Toward a consensus map of science , 2009, J. Assoc. Inf. Sci. Technol..

[14]  Timothy Cribbin,et al.  Visualizing and tracking the growth of competing paradigms: Two case studies , 2002, J. Assoc. Inf. Sci. Technol..

[15]  Loet Leydesdorff,et al.  Clusters and Maps of Science Journals Based on Bi-connected Graphs in the Journal Citation Reports , 2009, ArXiv.

[16]  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..

[17]  Henk F. Moed,et al.  Mapping of science by combined co-citation and word analysis, I. Structural aspects , 1991, J. Am. Soc. Inf. Sci..

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