Geographical knowledge diffusion and spatial diversity citation rank

This paper proposes a citation rank based on spatial diversity (SDCR) in terms of cities and countries, focusing on the measurement of the “spatial” aspect in citation networks. Our main goal is to solve the citation bias caused by different geographical locations of citations. We empirically investigate spatial properties of citing distances, citation patterns and spatial diversity to understand geographical knowledge diffusion, based on the data from “Transportation Science and Technology” subject category in the Web of Science (1966–2009). We also compare the proposed ranking method with other bibliometric measures, and conduct a case study to figure out the recent ranks of the well-established authors in Transportation research. It is found that the SDCR of a focal author is highly correlated with the sum of spatial diversity weights (“strength”) of all his in-links, and it is better to set the damping factors smaller than 0.75 when ranking authors with various initial academic years by SDCR. The cases show that Hong Kong is becoming a cluster in Transportation research.

[1]  Andreas Pyka,et al.  Innovation Networks. New Approaches in Modelling and Analyzing , 2005 .

[2]  Lutz Bornmann,et al.  Are there better indices for evaluation purposes than the h index? A comparison of nine different variants of the h index using data from biomedicine , 2008, J. Assoc. Inf. Sci. Technol..

[3]  Sergey Brin,et al.  The Anatomy of a Large-Scale Hypertextual Web Search Engine , 1998, Comput. Networks.

[4]  S. Breschi,et al.  Mobility of Skilled Workers and Co-Invention Networks: An Anatomy of Localized Knowledge Flows , 2009 .

[5]  Weimao Ke,et al.  Mapping the diffusion of scholarly knowledge among major U.S. research institutions , 2006, Scientometrics.

[6]  L. Egghe.  Power Laws in the Information Production Process: Lotkaian Informetrics , 2005 .

[7]  Henk F. Moed,et al.  Citation Analysis in Research Evaluation , 1899 .

[8]  Zi-Lin He.  International collaboration does not have greater epistemic authority , 2009, J. Assoc. Inf. Sci. Technol..

[9]  Wolfgang Glänzel,et al.  Cross-national preference in co-authorship, references and citations , 2006, Scientometrics.

[10]  D. King.  The scientific impact of nations , 2004, Nature.

[11]  Akbar Zaheer,et al.  Geography, Networks, and Knowledge Flow , 2007, Organ. Sci..

[12]  Ingo Liefner,et al.  Structural Holes and New Dimensions of Distance: The Spatial Configuration of the Scientific Knowledge Network of China's Optical Technology Sector , 2011 .

[13]  Michael Schreiber,et al.  How to modify the g-index for multi-authored manuscripts , 2010, J. Informetrics.

[14]  T. Wang,et al.  Measuring regional science networks in China: a comparison of international and domestic bibliographic data sources , 2011, Scientometrics.

[15]  Leo Egghe,et al.  The Hirsch index and related impact measures , 2010, Annu. Rev. Inf. Sci. Technol..

[16]  H. Moed.  Citation Analysis in Research Evaluation (Information Science & Knowledge Management) , 2005 .

[17]  Koen Frenken,et al.  The geographical and institutional proximity of research collaboration , 2007 .

[18]  Santo Fortunato,et al.  Diffusion of scientific credits and the ranking of scientists , 2009, Physical review. E, Statistical, nonlinear, and soft matter physics.

[19]  Liying Yang,et al.  Mapping institutions and their weak ties in a specialty: A case study of cystic fibrosis body composition research , 2009, Scientometrics.

[20]  Mark E. J. Newman,et al.  Power-Law Distributions in Empirical Data , 2007, SIAM Rev..

[21]  Sergei Maslov,et al.  Finding scientific gems with Google's PageRank algorithm , 2006, J. Informetrics.

[22]  Andrew M. Odlyzko,et al.  The Size and Growth Rate of the Internet , 1999, First Monday.

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

[24]  Annette Winkel Schwarz,et al.  The Top-level Global Research System, 1997-99: Centres, Networks and Nodality. An Analysis Based on Bibliometric Indicators , 2002 .

[25]  Johan Bollen,et al.  Refining dermatology journal impact factors using PageRank. , 2007, Journal of the American Academy of Dermatology.

[26]  James Caverlee,et al.  PageRank for ranking authors in co-citation networks , 2009, J. Assoc. Inf. Sci. Technol..

[27]  J. E. Hirsch,et al.  An index to quantify an individual's scientific research output , 2005, Proc. Natl. Acad. Sci. USA.

[28]  Yi Zhao,et al.  Bringing PageRank to the citation analysis , 2008, Inf. Process. Manag..

[29]  Mike Thelwall,et al.  The most highly cited Library and Information Science articles: Interdisciplinarity, first authors and citation patterns , 2007, Scientometrics.

[30]  Jarno Hoekman,et al.  Death of Distance in Science? A Gravity Approach to Research Collaboration , 2009 .

[31]  Ronald Rousseau,et al.  In those fields where multiple authorship is the rule, the h-index should be supplemented by role-based h-indices , 2010, J. Inf. Sci..

[32]  Massimo Franceschet,et al.  A cluster analysis of scholar and journal bibliometric indicators , 2009, J. Assoc. Inf. Sci. Technol..

[33]  R. Sinnott.  Virtues of the Haversine , 1984 .

[34]  Jorge E. Hirsch,et al.  An index to quantify an individual’s scientific research output that takes into account the effect of multiple coauthorship , 2009, Scientometrics.

[35]  Mark E. J. Newman.  A measure of betweenness centrality based on random walks , 2005, Soc. Networks.

[36]  Loet Leydesdorff,et al.  Mapping the geography of science: Distribution patterns and networks of relations among cities and institutes , 2010, J. Assoc. Inf. Sci. Technol..

[37]  Jarno Hoekman,et al.  Spatial scientometrics: Towards a cumulative research program , 2009, J. Informetrics.