The dynamics of triads in aggregated journal-journal citation relations: Specialty developments at the above-journal level

Dyads of journals—related by citations—can agglomerate into specialties through the mechanism of triadic closure. Using the Journal Citation Reports 2011, 2012, and 2013, we analyze triad formation as indicators of integration (specialty growth) and disintegration (restructuring). The strongest integration is found among the large journals that report on studies in different scientific specialties, such as PLoS ONE, Nature Communications, Nature, and Science. This tendency toward large-scale integration has not yet stabilized. Using the Islands algorithm, we also distinguish 51 local maxima of integration. We zoom into the cited articles that carry the integration for: (i) a new development within high-energy physics and (ii) an emerging interface between the journals Applied Mathematical Modeling and the International Journal of Advanced Manufacturing Technology. In the first case, integration is brought about by a specific communication reaching across specialty boundaries, whereas in the second, the dyad of journals indicates an emerging interface between specialties. These results suggest that integration picks up substantive developments at the specialty level. An advantage of the bottom-up method is that no ex ante classification of journals is assumed in the dynamic analysis.

[1]  Loet Leydesdorff,et al.  The use of percentiles and percentile rank classes in the analysis of bibliometric data: Opportunities and limits , 2012, J. Informetrics.

[2]  John Scott What is social network analysis , 2010 .

[3]  E. Holtzman,et al.  The Cancer Mission: Social Contexts of Biomedical Research , 1980 .

[4]  Kevin W. Boyack,et al.  Approaches to understanding and measuring interdisciplinary scientific research (IDR): A review of the literature , 2011, J. Informetrics.

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

[6]  Vladimir Batagelj,et al.  Social Network Analysis, Large-Scale , 2009, Encyclopedia of Complexity and Systems Science.

[7]  T. Snijders Statistical Models for Social Networks , 2011 .

[8]  Ismael Rafols,et al.  How journal rankings can suppress interdisciplinary research: A comparison between Innovation Stud , 2012 .

[9]  Ismael Rafols,et al.  How journal rankings can suppress interdisciplinarity. The case of innovation studies in business and management , 2011, ArXiv.

[10]  Santo Fortunato,et al.  Triadic closure as a basic generating mechanism of the structure of complex networks , 2014, Physical review. E, Statistical, nonlinear, and soft matter physics.

[11]  Ludo Waltman,et al.  Field-normalized citation impact indicators using algorithmically constructed classification systems of science , 2015, J. Informetrics.

[12]  G. Simmel The Number of Members as Determining the Sociological Form of the Group. I , 1902, American Journal of Sociology.

[13]  Renaud Lambiotte,et al.  Communities, knowledge creation, and information diffusion , 2009, J. Informetrics.

[14]  Mark S. Granovetter The Strength of Weak Ties , 1973, American Journal of Sociology.

[15]  Kevin W. Boyack,et al.  Coco at the Copacabana: Introducing Co-cited Author Pair Co-citation (Coco) Analysis , 2009 .

[16]  Barry Wellman,et al.  Does citation reflect social structure?: Longitudinal evidence from the Globenet interdisciplinary research group , 2004, J. Assoc. Inf. Sci. Technol..

[17]  Bethany S. Dohleman Exploratory social network analysis with Pajek , 2006 .

[18]  R. Whitley The Intellectual and Social Organization of the Sciences (Second Edition: with new introductory chapter entitled 'Science Transformed? The Changing Nature of Knowledge Production at the End of the Twentieth Century') , 1984 .

[19]  Wolfgang Glänzel,et al.  Using ‘core documents’ for detecting and labelling new emerging topics , 2011, Scientometrics.

[20]  F. Harary,et al.  Cluster Inference by using Transitivity Indices in Empirical Graphs , 1982 .

[21]  Steven B. Andrews,et al.  Structural Holes: The Social Structure of Competition , 1995, The SAGE Encyclopedia of Research Design.

[22]  Stanley Wasserman,et al.  Social Network Analysis: Methods and Applications , 1994, Structural analysis in the social sciences.

[23]  R. Breiger The Duality of Persons and Groups , 1974 .

[24]  A. Rapoport,et al.  A study of a large sociogram II. Elimination of free parameters , 2007 .

[25]  J. McGreevy Holographic Duality with a View Toward Many-Body Physics , 2009, 0909.0518.

[26]  Min-Yen Kan,et al.  Identifying research facilitators in an emerging Asian Research Area , 2013, Scientometrics.

[27]  Santo Fortunato,et al.  Community detection in graphs , 2009, ArXiv.

[28]  Loet Leydesdorff,et al.  Can “hot spots” in the sciences be mapped using the dynamics of aggregated journal–journal citation Relations? , 2015, J. Assoc. Inf. Sci. Technol..

[29]  Carl T. Bergstrom,et al.  Mapping Change in Large Networks , 2008, PloS one.

[30]  Peter Rodgers,et al.  eulerAPE: Drawing Area-Proportional 3-Venn Diagrams Using Ellipses , 2014, PloS one.

[31]  Vladimir Batagelj,et al.  Short cycle connectivity , 2007, Discret. Math..

[32]  Mark Newman,et al.  Networks: An Introduction , 2010 .

[33]  Ismael Rafols,et al.  Indicators of the interdisciplinarity of journals: Diversity, centrality, and citations , 2010, J. Informetrics.

[34]  Loet Leydesdorff,et al.  Dynamic animations of journal maps: Indicators of structural changes and interdisciplinary developments , 2009, J. Assoc. Inf. Sci. Technol..

[35]  Hareesha Mk,et al.  "Environmentalism and Forest Rights of Tribals in Dakshina Kannada, Udupi and Uttara Kannada Districts of Karnataka " , 2009 .