Encyclopedia of Social Network Analysis and Mining

Living Edition
| Editors: Reda Alhajj, Jon Rokne

Scholarly Network Analysis

  • Erjia Yan
  • Ying Ding
Living reference work entry
DOI: https://doi.org/10.1007/978-1-4614-7163-9_249-1



Node (in scholarly networks)

Units such as words, papers, patents, authors, journals, institutions, fields, and countries

Edge (in scholarly networks)

Citation, co-citation, co-word, coauthor, bibliographic coupling, hybrid, or heterogeneous relations

Scholarly network

The combination of edge properties and node properties defines a scholarly network

Macro-level approach

Statistics that are used to identify the global structural features of networks, including component, bicomponent, shortest distance, clustering coefficient, degree distribution, and error and attack tolerance

Meso-level approach

Approaches that focus on the behaviors of a group of actors, including topic identification and community detection

Microlevel approach

Indicators that are useful to understand individual node’s power, stratification,...


Collaboration Network Citation Network Scientific Collaboration Knowledge Flow Scholarly Communication 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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  1. Bergstrom CT, West JD (2008) Assessing citations with the Eigenfactor™ metrics. Neurology 71(23):1850–1851CrossRefGoogle Scholar
  2. Bettencourt LMA, Kaiser DI, Kaur J, Castillo-Chávez C, Wojick DE (2008) Population modeling of the emergence and development of scientific fields. Scientometrics 75(3):495–518CrossRefGoogle Scholar
  3. Blei DM, Ng AY, Jordan MI (2003) Latent Dirichlet allocation. J Mach Learn Res 3(4–5):993–1033MATHGoogle Scholar
  4. Bollen J, Rodriguez MA, Van de Sompel H (2006) Journal status. Scientometrics 69(3):669–687CrossRefGoogle Scholar
  5. Boyack KW, Klavans AR, Börner K (2005) Mapping the backbone of science. Scientometrics 64(3):351–374CrossRefGoogle Scholar
  6. Brin S, Page L (1998) The anatomy of a large-scale hypertextual web search engine. Comput Netw ISDN Syst 30(117):107CrossRefGoogle Scholar
  7. Cowan R, Jonard N (2004) Network structure and the diffusion of knowledge. J Econ Dyn Control 28(8):1557–1575MathSciNetCrossRefMATHGoogle Scholar
  8. Freeman LC (1979) Centrality in social networks: conceptual clarification. Soc Netw 1(3):215–239MathSciNetCrossRefGoogle Scholar
  9. Herrera M, Roberts DC, Gulbahce N (2010) Mapping the evolution of scientific fields. PLoS ONE 5(5):6CrossRefGoogle Scholar
  10. Hirsch JE (2005) An index to quantify an individual's scientific research output. Proc Natl Acad Sci USA 102(46):16569–16572CrossRefMATHGoogle Scholar
  11. Jaffe AB, Trajtenberg M, Henderson AD (1993) Geographical localization of knowledge spillovers by patent citations. Q J Econ 108(3):577–599CrossRefGoogle Scholar
  12. Kessler MM (1963) Bibliographic coupling between scientific papers. Am Doc 14(1):10–25CrossRefGoogle Scholar
  13. Kiss IZ, Broom M, Craze PG, Rafols I (2010) Can epidemic models describe the diffusion of topics across disciplines? J Informet 4(1):74–82CrossRefGoogle Scholar
  14. Leydesdorff L, Persson O (2010) Mapping the geography of science: distribution patterns and networks of relations among cities and institutes. J Am Soc Inf Sci Technol 61(8):1622–1634Google Scholar
  15. Newman MEJ (2003) The structure and function of complex networks. SIAM Rev 45(2):167–256MathSciNetCrossRefMATHGoogle Scholar
  16. Newman M, Girvan M (2004) Finding and evaluating community structure in networks. Phys Rev E 69(2):026113CrossRefGoogle Scholar
  17. Nooy W, Mrvar A, Batagelj V (2005) Exploratory social network analysis with Pajek. Cambridge University Press, CambridgeCrossRefGoogle Scholar
  18. Pinski G, Narin F (1976) Citation influence for journal aggregates of scientific publications: theory, with application to the literature of physics. Inf Process Manag 12(5):297–312CrossRefGoogle Scholar
  19. Porter AL, Roessner JD, Cohen AS, Perreault M (2006) Interdisciplinary research: meaning, metrics and nurture. Res Eval 15(3):187–195CrossRefGoogle Scholar
  20. Radicchi F, Fortunato S, Markines B, Vespignani A (2009) Diffusion of scientific credits and the ranking of scientists. Phys Rev E 80(5):056103CrossRefGoogle Scholar
  21. Rafols I, Meyer M (2010) Diversity and network coherence as indicators of interdisciplinarity: case studies in bionanoscience. Scientometrics 82(2):263–287CrossRefGoogle Scholar
  22. Rinia EJ, Van Leeuwen TN, Bruins EEW, Van Vuren HG, Van Raan AFJ (2002) Measuring knowledge transfer between fields of science. Scientometrics 54(3):347–362CrossRefGoogle Scholar
  23. Rosvall M, Bergstrom CT (2008) Maps of information flow reveal community structure in complex networks. Proc Natl Acad Sci USA 105(4):1118–1123CrossRefGoogle Scholar
  24. SCImago (2007) SJR: SCImago Journal & Country Rank. http://www.scimagojr.com. Retrieved 31 Aug 2009
  25. Seidman SB (1983) Network structure and minimum degree. Soc Netw 5:269–287MathSciNetCrossRefGoogle Scholar
  26. Small H (1973) Co-citation in the scientific literature: A new measure of the relationship between two documents. J Am Soc Inf Sci 24(4):265–269MathSciNetCrossRefGoogle Scholar
  27. Sun Y, Norick B, Han J, Yan X, Yu PS, Yu X (2013) Pathselclus: Integrating meta-path selection with user-guided object clustering in heterogeneous information networks. ACM Trans Knowl Discov Data (TKDD) 7(3):11Google Scholar
  28. Walker D, Xie H, Yan KK, Maslov S (2007) Ranking scientific publications using a simple model of network traffic. J Stat Mech: Theory Exp P06010. doi:10.1088/1742-5468/2007/06/P06010Google Scholar
  29. Waltman L, Van Eck NJ, Noyons ECM (2010) A unified approach to mapping and clustering of bibliometric networks. J Informetr 4(4):629–635CrossRefGoogle Scholar
  30. Waltman L, Yan E (2014) PageRank-related methods for analyzing citation networks. In: Ding Y, Rousseau R, Wolfram D (eds) Measuring scholarly impact. Springer International Publishing, Cham, pp 83–100Google Scholar
  31. White HD, McCain KW (1998) Visualizing a discipline: an author co-citation analysis of information science 1972–1995. J Am Soc Inf Sci 49(4):327–355Google Scholar
  32. Yan E, Ding Y (2012) Scholarly network similarities: how bibliographic coupling networks, citation networks, co-citation networks, topical networks, coauthorship networks, and co-word networks relate to each other. J Am Soc Inf Sci Technol 63(7):1313–1326CrossRefGoogle Scholar
  33. Yan E, Ding Y, Sugimoto CR (2011) P-Rank: an indicator measuring prestige in heterogeneous scholarly networks. J Am Soc Inf Sci Technol 62(3):467–477Google Scholar
  34. Yan E, Ding Y, Cronin B, Leydesdorff L (2013) A bird’s eye view of scientific trading: dependency relations among fields of science. J Informetr 7(2):249–264CrossRefGoogle Scholar
  35. Yan E (2015) Disciplinary knowledge production and diffusion in science. J Assoc Inf Sci Technol. doi:10.1002/asi.23541Google Scholar
  36. Yan E, Yu Q (2015) Using path-based approaches to examine the dynamic structure of discipline-level citation networks: 1997–2011. J Assoc Inf Sci Technol. doi:10.1002/asi.23516Google Scholar
  37. Yin L, Kretschmer H, Hanneman RA, Liu Z (2006) Connection and stratification in research collaboration: an analysis of the COLLNET network. Inf Process Manag 42(6):1599–1613CrossRefGoogle Scholar
  38. Zhang L, Liu X, Janssens F, Liang L, Glänzel W (2010) Subject clustering analysis based on ISI category classification. J Informetr 4(2):185–193CrossRefGoogle Scholar
  39. Zhuang E, Chen G, Feng G (2011) A network model of knowledge accumulation through diffusion and upgrade. Physica A: Statistical Mechanics and its Applications 390(13):2582–2592CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media LLC 2016

Authors and Affiliations

  1. 1.College of Computing and InformaticsDrexel UniversityPhiladelphiaUSA
  2. 2.School of Informatics and ComputingIndiana UniversityBloomingtonUSA