Advertisement

Scientometrics

, Volume 101, Issue 2, pp 1345–1360 | Cite as

Comparative study on structure and correlation among author co-occurrence networks in bibliometrics

  • Jun-Ping Qiu
  • Ke Dong
  • Hou-Qiang Yu
Article

Abstract

This paper introduces author-level bibliometric co-occurrence network by discussing its history and contribution to the analysis of scholarly communication and intellectual structure. The difference among various author co-occurrence networks, which type of network shall be adapted in different situations, as well as the relationship among these networks, however, remain not explored. Five types of author co-occurrence networks were proposed: (1) co-authorship (CA); (2) author co-citation (ACC); (3) author bibliographic coupling (ABC); (4) words-based author coupling (WAC); (5) journals-based author coupling (JAC). Networks of 98 high impact authors from 30 journals indexed by 2011 version of Journal Citation Report-SSCI under the Information Science & Library Science category are constructed for study. Social network analysis and hierarchical cluster analysis are applied to identify sub-networks with results visualized by VOSviewer software. QAP test is used to find potential correlation among networks. Cluster analysis results show that all the five types of networks have the power for revealing intellectual structure of sciences but the revealed structures are different from each other. ABC identified more sub-structures than other types of network, followed by CA and ACC. WAC result is easily affected and JAC result is ambiguous. QAP test result shows that ABC network has the highest proximity with other types of networks while CA network has relatively lower proximity with other networks. This paper will provide a better comprehension of author interaction and contribute to cognitive application of author co-occurrence network analysis.

Keywords

Co-authorship analysis Author co-citation analysis Author bibliographic coupling Correlation analysis Bibliometrics 

Notes

Acknowledgments

This paper is supported by the Major Program of the National Social Science Foundation of China (Grant No. 11&ZD152) and Humanities and Social Sciences project of Wuhan University (Grant No. 2012GSP032).

References

  1. Acedo, F. J., Barroso, C., Casanueva, C., & Galán, J. L. (2006). Co-authorship in management and organizational studies: an empirical and network analysis. Journal of Management Studies, 43(5), 957–983.CrossRefGoogle Scholar
  2. Ahlgren, P., Jarneving, B., & Rousseau, R. (2003). Requirements for a cocitation similarity measure, with special reference to Pearson’s correlation coefficient. Journal of the American Society for Information Science and Technology, 54(6), 550–560.CrossRefGoogle Scholar
  3. Borgatti, S., Everett, M., & Freeman, L. (2002). UCINET 6 for Windows: Software for social network analysis (Version 6.102). Harvard: Analytic Technologies.Google Scholar
  4. Boyack, K. W., & Klavans, R. (2010). Co-citation analysis, bibliographic coupling, and direct citation: Which citation approach represents the research front most accurately? Journal of the American Society for Information Science and Technology, 61(12), 2389–2404.CrossRefGoogle Scholar
  5. Cabanac, G. (2011). Accuracy of inter-researcher similarity measures based on topical and social clues. Scientometrics, 87(3), 597–620.CrossRefGoogle Scholar
  6. Chen, L.-C., & Lien, Y.-H. (2011). Using author co-citation analysis to examine the intellectual structure of e-learning: A MIS perspective. Scientometrics, 89(3), 867–886.CrossRefGoogle Scholar
  7. Chen, C., Paul, R. J., & O’Keefe, B. (2001). Fitting the jigsaw of citation: Information visualization in domain analysis. Journal of the American Society for Information Science and Technology, 52(4), 315–330.CrossRefGoogle Scholar
  8. de Nooy, W., Mrvar, A., & Batagelj, V. (2005). Exploratory social network analysis with Pajek (Vol. 27). Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  9. de Solla Price, D. J., & Beaver, D. (1966). Collaboration in an invisible college. American Psychologist, 21(11), 1011.CrossRefGoogle Scholar
  10. Ding, Y. (2011). Scientific collaboration and endorsement: Network analysis of coauthorship and citation networks. Journal of informetrics, 5(1), 187–203.CrossRefGoogle Scholar
  11. Ding, Y., & Cronin, B. (2011). Popular and/or prestigious? Measures of scholarly esteem. Information Processing and Management, 47(1), 80–96.CrossRefGoogle Scholar
  12. Egghe, L., & Leydesdorff, L. (2009). The relation between Pearson’s correlation coefficient r and Salton’s cosine measure. Journal of the American Society for Information Science and Technology, 60(5), 1027–1036.CrossRefGoogle Scholar
  13. Eslami, H., Ebadi, A., & Schiffauerova, A. (2013). Effect of collaboration network structure on knowledge creation and technological performance: The case of biotechnology in Canada. Scientometrics, 97(1), 99–119.CrossRefGoogle Scholar
  14. Fox, M. F. (2008). Collaboration between science and social science: Issues, challenges, and opportunities. Research in Social Problems and Public Policy, 16, 17–30.CrossRefGoogle Scholar
  15. Garfield, E. (1972). Citation analysis as a tool in journal evaluation. American Association for the Advancement of Science.Google Scholar
  16. Garfield, E. (1996). Significant scientific literature appears in a small core of journals: Scientist, Incorporated.Google Scholar
  17. Garfield, E., & Merton, R. K. (1979). Citation indexing: Its theory and application in science, technology, and humanities (Vol. 8). New York: Wiley.Google Scholar
  18. Gazni, A., & Didegah, F. (2011). Investigating different types of research collaboration and citation impact: A case study of Harvard University’s publications. Scientometrics, 87(2), 251–265.CrossRefGoogle Scholar
  19. Groh, G., & Fuchs, C. (2011). Multi-modal social networks for modeling scientific fields. Scientometrics, 89(2), 569–590.CrossRefGoogle Scholar
  20. He, T. (2009). International scientific collaboration of China with the G7 countries. Scientometrics, 80(3), 571–582.CrossRefGoogle Scholar
  21. Hubert, L., & Schultz, J. (1976). Quadratic assignment as a general data analysis strategy. British Journal of Mathematical and Statistical Psychology, 29(2), 190–241.Google Scholar
  22. Johnson, B., & Oppenheim, C. (2007). How socially connected are citers to those that they cite? Journal of Documentation, 63(5), 609–637.Google Scholar
  23. Kessler, M. M. (1963). Bibliographic coupling between scientific papers. American Documentation, 14(1), 10–25.CrossRefGoogle Scholar
  24. Kim, S., & Cho, S. (2013). Characteristics of Korean personal names. Journal of the American Society for Information Science and Technology, 64(1), 86–95.CrossRefGoogle Scholar
  25. Kretschmer, H. (2004). Author productivity and geodesic distance in bibliographic co-authorship networks, and visibility on the Web. Scientometrics, 60(3), 409–420.CrossRefGoogle Scholar
  26. Lee, S., & Bozeman, B. (2005). The impact of research collaboration on scientific productivity. Social Studies of Science, 35(5), 673–702.CrossRefGoogle Scholar
  27. Leydesdorff, L., & Vaughan, L. (2006). Co-occurrence matrices and their applications in information science: Extending ACA to the Web environment. Journal of the American Society for Information Science and Technology, 57(12), 1616–1628.CrossRefGoogle Scholar
  28. Lin, W.-Y. C., & Huang, M.-H. (2012). The relationship between co-authorship, currency of references and author self-citations. Scientometrics, 90(2), 343–360.CrossRefGoogle Scholar
  29. Ma, R. (2012). Author bibliographic coupling analysis: A test based on a Chinese academic database. Journal of Informetrics, 6(4), 532–542.CrossRefGoogle Scholar
  30. McCain, K. W. (1990). Mapping authors in intellectual space: A technical overview. Journal of the American Society for Information Science, 41(6), 433–443.CrossRefGoogle Scholar
  31. Newman, M. E. (2001a). Scientific collaboration networks. I. Network construction and fundamental results. Physical Review E, 64 (1), 016131.Google Scholar
  32. Newman, M. E. (2001b). Scientific collaboration networks. II. Shortest paths, weighted networks, and centrality. Physical Review E, 64 (1), 016132.Google Scholar
  33. Newman, M. E. (2001c). The structure of scientific collaboration networks. Proceedings of the National Academy of Sciences, 98(2), 404–409.MathSciNetCrossRefzbMATHGoogle Scholar
  34. Newman, M. E. (2004). Coauthorship networks and patterns of scientific collaboration. Proceedings of the National Academy of Sciences of the United States of America, 101(Suppl 1), 5200–5205.CrossRefGoogle Scholar
  35. Ni, C., Sugimoto, C. R., & Cronin, B. (2013a). Visualizing and comparing four facets of scholarly communication: producers, artifacts, concepts, and gatekeepers. Scientometrics, 94 (3), 1161–1173.Google Scholar
  36. Ni, C., Sugimoto, C. R., & Jiang, J. (2013b). Venue‐author‐coupling: A measure for identifying disciplines through author communities. Journal of the American Society for Information Science and Technology, 64 (2), 265–279.Google Scholar
  37. Otte, E., & Rousseau, R. (2002). Social network analysis: A powerful strategy, also for the information sciences. Journal of information Science, 28(6), 441–453.CrossRefGoogle Scholar
  38. Rousseau, R. (2010). Bibliographic coupling and co-citation as dual notions. A Festschrift in Honour of Peter Ingwersen, Special Volume of the e-Zine of the ISSI, 2010, 173–183.MathSciNetGoogle Scholar
  39. Salton, G. (1989). Automatic text processing: The transformation, analysis, and retrieval of information by computer. Reading: Addison-Wesley.Google Scholar
  40. Schneider, J. W., Larsen, B., & Ingwersen, P. (2009). A comparative study of first and all-author co-citation counting, and two different matrix generation approaches applied for author co-citation analyses. Scientometrics, 80(1), 103–130.CrossRefGoogle Scholar
  41. Small, H. (1973). Co-citation in the scientific literature: A new measure of the relationship between two documents. Journal of the American Society for Information Science, 24(4), 265–269.CrossRefGoogle Scholar
  42. Song, M., & Kim, S. (2013). Detecting the knowledge structure of bioinformatics by mining full-text collections. Scientometrics, 96(1), 183–201.CrossRefGoogle Scholar
  43. Sooryamoorthy, R. (2009). Do types of collaboration change citation? Collaboration and citation patterns of South African science publications. Scientometrics, 81(1), 177–193.CrossRefGoogle Scholar
  44. Strotmann, A., & Bleier, A. (2013). Author name co-mention analysis: Testing a poor man’s author co-citation analysis method. arXiv preprint arXiv:1309.5256.Google Scholar
  45. Tang, J., Zhang, J., Yao, L., Li, J., Zhang, L., & Su, Z. (2008). ArnetMiner: extraction and mining of academic social networks. Paper presented at the Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining.Google Scholar
  46. Thijs, B., & Glänzel, W. (2010). A structural analysis of collaboration between European research institutes. Research Evaluation, 19(1), 55–65.CrossRefGoogle Scholar
  47. Torvik, V. I., Weeber, M., Swanson, D. R., & Smalheiser, N. R. (2005). A probabilistic similarity metric for medline records: A model for author name disambiguation. Journal of the American Society for Information Science and Technology, 56(2), 140–158.CrossRefGoogle Scholar
  48. Van Eck, N. J., & Waltman, L. (2008). Appropriate similarity measures for author co-citation analysis. Journal of the American Society for Information Science and Technology, 59(10), 1653–1661.CrossRefGoogle Scholar
  49. Van Eck, N. J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523–538.CrossRefGoogle Scholar
  50. van Rijnsoever, F. J., Hessels, L. K., & Vandeberg, R. L. (2008). A resource-based view on the interactions of university researchers. Research Policy, 37(8), 1255–1266.CrossRefGoogle Scholar
  51. Wagner, C. S. (2005). Six case studies of international collaboration in science. Scientometrics, 62(1), 3–26.CrossRefGoogle Scholar
  52. Wallace, M. L., Larivière, V., & Gingras, Y. (2012). A small world of citations? The influence of collaboration networks on citation practices. PLoS One, 7(3), e33339.CrossRefGoogle Scholar
  53. White, H. D. (2003). Pathfinder networks and author cocitation analysis: A remapping of paradigmatic information scientists. Journal of the American Society for Information Science and Technology, 54(5), 423–434.CrossRefGoogle Scholar
  54. White, H. D., & Griffith, B. C. (1981). Author cocitation: A literature measure of intellectual structure. Journal of the American Society for information Science, 32(3), 163–171.CrossRefGoogle Scholar
  55. White, H. D., & Griffith, B. C. (1982). Authors as markers of intellectual space: Co-citation in studies of science, technology and society. Journal of Documentation, 38(4), 255–272.CrossRefGoogle Scholar
  56. White, H. D., & McCain, K. W. (1998). Visualizing a discipline: An author co-citation analysis of information science, 1972–1995. Journal of the American Society for Information Science, 49(4), 327–355.Google Scholar
  57. White, H. D., Wellman, B., & Nazer, N. (2004). Does citation reflect social structure?: Longitudinal evidence from the “Globenet” interdisciplinary research group. Journal of the American Society for Information Science and Technology, 55(2), 111–126.CrossRefGoogle Scholar
  58. Yan, E., & Ding, Y. (2009). Applying centrality measures to impact analysis: A coauthorship network analysis. Journal of the American Society for Information Science and Technology, 60(10), 2107–2118.CrossRefGoogle Scholar
  59. Yan, E., & Ding, Y. (2012). Scholarly network similarities: How bibliographic coupling networks, citation networks, cocitation networks, topical networks, coauthorship networks, and coword networks relate to each other. Journal of the American Society for Information Science and Technology, 63(7), 1313–1326.CrossRefGoogle Scholar
  60. Zhao, D., & Strotmann, A. (2008a). Comparing all-author and first-author co-citation analyses of information science. Journal of Informetrics, 2(3), 229–239.CrossRefGoogle Scholar
  61. Zhao, D., & Strotmann, A. (2008b). Evolution of research activities and intellectual influences in information science 1996–2005: Introducing author bibliographic-coupling analysis. Journal of the American Society for Information Science and Technology, 59(13), 2070–2086.CrossRefGoogle Scholar
  62. Zhao, D., & Strotmann, A. (2008c). Information science during the first decade of the web: An enriched author cocitation analysis. Journal of the American Society for Information Science and Technology, 59(6), 916–937.CrossRefGoogle Scholar
  63. Zitt, M., Lelu, A., & Bassecoulard, E. (2011). Hybrid citation-word representations in science mapping: Portolan charts of research fields? Journal of the American Society for Information Science and Technology, 62(1), 19–39.CrossRefGoogle Scholar

Copyright information

© Akadémiai Kiadó, Budapest, Hungary 2014

Authors and Affiliations

  1. 1.School of Information ManagementWuhan UniversityWuhanChina

Personalised recommendations