Advertisement

Scientometrics

, Volume 113, Issue 2, pp 845–865 | Cite as

Community evolution analysis based on co-author network: a case study of academic communities of the journal of “Annals of the Association of American Geographers”

  • Jie ZhengEmail author
  • Jianya Gong
  • Rui LiEmail author
  • Kai Hu
  • Huayi Wu
  • Siluo Yang
Article

Abstract

Academic community evolution reveals the development of scientific collaboration among scientists. These social interactions of researchers can be well reflected by co-author network, making it feasible to investigate academic community through looking into co-author network, and to study community evolution through dynamic co-author network analysis. Existing metrics measure an author’s impact or centrality in co-author network individually, rather than considering the academic community as a whole. Besides, co-authors of a paper usually make different contributions reflected in the name order, which is often ignored in traditional co-author network analysis. Furthermore, attention has been paid mainly on those structure-level characteristics like the small-world coefficient and the clustering coefficient, the content-level characteristics like community, author, and topics, however, are crucial in the understanding of community evolution. To address those problems, we firstly propose a “comprehensive impact index” to evaluate the author in a co-author network by comprehensively considering the statistic-based impact and the network-based centrality. Then the comprehensive index value of all authors in a community is added up to evaluate the community as a whole. Further, a lifecycle strategy is proposed for the community evolution analysis. Taking geography academic community as a pilot study, we select 919 co-authored papers from the flagship journal of “Annals of the Association of American Geographers”. The co-author groups are generated by community detection method. Top three co-author groups are identified through computing with the proposed index and analyzed through the proposed lifecycle strategy from perspective of community structures, member authors, and impacts respectively. The results demonstrate our proposed index and strategy are more efficient for analyzing academic community evolution than traditional methods.

Keywords

Annals of the Association of American Geographers Co-author network Community detection Lifecycle analysis 

Notes

Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant Nos. 41371370; 41371372), the Major State Research Development Program of China (Grant No. 2016YFB0502301), and the Grand Special of High Resolution On Earth Observation: Application demonstration system of high resolution remote sensing and transportation (Grant No: 07-Y30B10-9001-14/16). Thanks Mr. Stephen C. McClure and Miss Julie Yu for helping us with the English revisions.

References

  1. Balling, R. C., & Wells, S. G. (1990). Historical rainfall patterns and arroyo activity within the Zuni River drainage basin, New Mexico. Annals of the Association of American Geographers, 80(4), 603–617.CrossRefGoogle Scholar
  2. Bastian, M., Heymann, S., & Jacomy, M. (2009). Gephi: An open source software for exploring and manipulating networks. ICWSM, 8, 361–362.Google Scholar
  3. Blondel, V. D., Guillaume, J.-L., Lambiotte, R., & Lefebvre, E. (2008). Fast unfolding of communities in large networks. Journal of Statistical Mechanics: Theory and Experiment, 2008(10), P10008. doi: 10.1088/1742-5468/2008/10/P10008.CrossRefGoogle Scholar
  4. Bonacich, P. (2010). Factoring and weighting approaches to status scores and clique identification. Journal of Mathematical Sociology, 2(1), 113–120.CrossRefGoogle Scholar
  5. Boran, F. E., Genç, S., Kurt, M., & Akay, D. (2009). A multi-criteria intuitionistic fuzzy group decision making for supplier selection with TOPSIS method. Expert Systems with Applications, 36(8), 11363–11368.CrossRefGoogle Scholar
  6. Bornmann, L., & Daniel, H.-D. (2005). Does the h-index for ranking of scientists really work? Scientometrics, 65(3), 391–392.CrossRefGoogle Scholar
  7. Caron, C., Roche, S., Goyer, D., & Jaton, A. (2008). GIScience journals ranking and evaluation: An international delphi study. Transactions in GIS, 12(3), 293–321.CrossRefGoogle Scholar
  8. Chen, C., & Morris, S. (2003). Visualizing evolving networks: Minimum spanning trees versus pathfinder networks. In  IEEE symposium on information visualization (IEEE Cat. No.03TH8714), 21 Oct 2003 (pp. 67–74).Google Scholar
  9. Chinchilla-Rodríguez, Z., Ferligoj, A., Miguel, S., Kronegger, L., & de Moya-Anegón, F. (2012). Blockmodeling of co-authorship networks in library and information science in Argentina: A case study. Scientometrics, 93(3), 699–717. doi: 10.1007/s11192-012-0794-6.CrossRefGoogle Scholar
  10. Cugmas, M., Ferligoj, A., & Kronegger, L. (2016). The stability of co-authorship structures. Scientometrics, 106(1), 163.CrossRefGoogle Scholar
  11. Dance, A. (2012). Authorship: Who’s on first? Nature, 489(7417), 591–593.CrossRefGoogle Scholar
  12. Danon, L., Diazguilera, A., Duch, J., & Arenas, A. (2005). Comparing community structure identification. Journal of Statistical Mechanics: Theory and Experiment, 2005(09), 09008.CrossRefGoogle Scholar
  13. De Haan, J. (1997). Authorship patterns in Dutch sociology. Scientometrics, 39(2), 197–208.CrossRefGoogle Scholar
  14. Garfield, E., & Merton, R. K. (1979). Citation indexing: Its theory and application in science, technology, and humanities (Vol. 8). New York: Wiley.Google Scholar
  15. Girvan, M., & Newman, M. E. J. (2002). Community structure in social and biological networks. Proceedings of the National Academy of Sciences USA, 99(12), 7821–7826.MathSciNetCrossRefzbMATHGoogle Scholar
  16. Golledge, R. G., Church, R., Dozier, J., Estes, J. E., Michaelsen, J., Sirnonett, D. S., et al. (1982). Commentary on “The highest form of the geographer’s art”. Annals of the Association of American Geographers, 72(4), 557–558.CrossRefGoogle Scholar
  17. Hagen, N. T. (2008). Harmonic allocation of authorship credit: Source-level correction of bibliometric bias assures accurate publication and citation analysis. PLoS ONE, 3(12), e4021.CrossRefGoogle Scholar
  18. Hagen, N. T. (2010). Harmonic publication and citation counting: Sharing authorship credit equitably—Not equally, geometrically or arithmetically. Scientometrics, 84(3), 785–793.CrossRefGoogle Scholar
  19. Hart, J. F. (1982). The highest form of the geographer’s art*. Annals of the Association of American Geographers, 72(1), 1–29.CrossRefGoogle Scholar
  20. Hirsch, J. E. (2005). An index to quantify an individual’s scientific research output. Proceedings of the National Academy of Sciences USA, 102(46), 16569.CrossRefzbMATHGoogle Scholar
  21. Hummon, N. P., & Dereian, P. (1989). Connectivity in a citation network: The development of DNA theory*. Social Networks, 11(1), 39–63.CrossRefGoogle Scholar
  22. Kernighan, B. W., & Lin, S. (1970). An efficient heuristic procedure for partitioning graphs. Bell System Technical Journal, 49(2), 291–307.CrossRefzbMATHGoogle Scholar
  23. Kronegger, L., Mali, F., Ferligoj, A., & Doreian, P. (2011). Collaboration structures in Slovenian scientific communities. Scientometrics, 90(2), 631–647.CrossRefGoogle Scholar
  24. Lee, S., & Bozeman, B. (2005). The impact of research collaboration on scientific productivity. Social Studies of Science, 35(5), 673–702.CrossRefGoogle Scholar
  25. Li, L., Liu, Y., Zhu, H., Ying, S., Luo, Q., Luo, H., et al. (2016). A bibliometric and visual analysis of global geo-ontology research. Computers & Geosciences, 99, 1–8.CrossRefGoogle Scholar
  26. Liang, X. (2015). The changing impact of geographic distance: A preliminary analysis on the co-author networks in scientometrics (1983–2013). In 48th Hawaii international conference on system sciences, 5–8 Jan 2015 (pp. 722–731).Google Scholar
  27. Liu, X., Bollen, J., Nelson, M. L., & Van de Sompel, H. (2005). Co-authorship networks in the digital library research community. Information Processing and Management, 41(6), 1462–1480.CrossRefGoogle Scholar
  28. Liu, C., & Gui, Q. (2016). Mapping intellectual structures and dynamics of transport geography research: A scientometric overview from 1982 to 2014. Scientometrics, 109(1), 159–184.CrossRefGoogle Scholar
  29. Mali, F., Kronegger, L., Doreian, P., & Ferligoj, A. (2012). Dynamic scientific co-authorship networks. In A. Scharnhorst, K. Börner & P. van den Besselaar (Eds.), Models of science dynamics: Encounters between complexity theory and information sciences (pp. 195–232). Berlin: Springer.CrossRefGoogle Scholar
  30. Mao, L. (2014). The geography, structure, and evolution of the GIS research community in the US: A network analysis from 1992 to 2011. Transactions in GIS, 18(5), 704–717.CrossRefGoogle Scholar
  31. Martin, G. J. (2005). All possible worlds: A history of geographical ideas. Oxford University Press. http://EconPapers.repec.org/RePEc:oxp:obooks:9780195168709.
  32. Mutschke, P. (2003). Mining networks and central entities in digital libraries. A graph theoretic approach applied to co-author networks. In M. R. Berthold, H.-J. Lenz, E. Bradley, R. Kruse & C. Borgelt (Eds.), Advances in intelligent data analysis V. 5th international symposium on intelligent data analysis, IDA 2003, Berlin, Germany, 28–30 Aug 2003 (pp. 155–166). Berlin: Springer.CrossRefGoogle Scholar
  33. Newman, M. E. J. (2006). Finding community structure in networks using the eigenvectors of matrices. Physical Review E, 74(3), 036104.MathSciNetCrossRefGoogle Scholar
  34. Newman, M. E., & Girvan, M. (2004). Finding and evaluating community structure in networks. Physical Review E, 69(2), 026113.CrossRefGoogle Scholar
  35. Peng, Y., Lin, A., Wang, K., Liu, F., Zeng, F., & Yang, L. (2015). Global trends in DEM-related research from 1994 to 2013: A bibliometric analysis. Scientometrics, 105(1), 347–366.CrossRefGoogle Scholar
  36. Said, Y. H., Wegman, E. J., Sharabati, W. K., & Rigsby, J. T. (2008). RETRACTED: Social networks of author–coauthor relationships. Computational Statistics & Data Analysis, 52(4), 2177–2184.MathSciNetCrossRefGoogle Scholar
  37. Savic, M., Ivanovic, M., Radovanovic, M., Ognjanovic, Z., Pejovic, A., & Kruger, T. J. (2014). The structure and evolution of scientific collaboration in Serbian mathematical journals. Scientometrics, 101(3), 1805–1830.CrossRefGoogle Scholar
  38. Skupin, A. (2004). The world of geography: Visualizing a knowledge domain with cartographic means. Proceedings of the National Academy of Sciences USA, 101, 5274–5278.CrossRefGoogle Scholar
  39. Wang, Y., Xiang, C., Zhao, P., Mao, G., & Du, H. (2016). A bibliometric analysis for the research on river water quality assessment and simulation during 2000–2014. Scientometrics, 108(3), 1333–1346.CrossRefGoogle Scholar
  40. Wasserman, S., & Faust, K. (1994). Social network analysis: Methods and applications. Cambridge: Cambridge University Press.CrossRefzbMATHGoogle Scholar
  41. Yan, E., & Ding, Y. (2009). Applying centrality measures to impact analysis: A coauthorship network analysis. Journal of the Association for Information Science and Technology, 60(10), 2107–2118.CrossRefGoogle Scholar
  42. Zaïane, O. R., Chen, J., & Goebel, R. (2009). Mining research communities in bibliographical data. In H. Zhang, M. Spiliopoulou, B. Mobasher, C. L. Giles, A. McCallum, O. Nasraoui et al. (Eds.), Advances in web mining and web usage analysis. 9th international workshop on knowledge discovery on the web, WebKDD 2007, and 1st international workshop on social networks analysis, SNA-KDD 2007, San Jose, CA, USA, 12–15 Aug 2007. Revised Papers (pp. 59–76). Berlin: Springer.CrossRefGoogle Scholar
  43. Zhang, C., Bu, Y., & Ding, Y. (2016). Understanding scientific collaboration from the perspective of collaborators and their network structures. In IConference 2016 Proceedings.Google Scholar

Copyright information

© Akadémiai Kiadó, Budapest, Hungary 2017

Authors and Affiliations

  1. 1.The State Key Laboratory of Information Engineering in Surveying, Mapping and Remote SensingWuhan UniversityWuhanChina
  2. 2.Collaborative Innovation Center of Geospatial TechnologyWuhan UniversityWuhanChina
  3. 3.School of Information ManagementWuhan UniversityWuhanChina

Personalised recommendations