Skip to main content
Log in

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”

  • Published:
Scientometrics Aims and scope Submit manuscript

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

References

  • 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.

    Article  Google Scholar 

  • Bastian, M., Heymann, S., & Jacomy, M. (2009). Gephi: An open source software for exploring and manipulating networks. ICWSM, 8, 361–362.

    Google Scholar 

  • 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.

    Article  Google Scholar 

  • Bonacich, P. (2010). Factoring and weighting approaches to status scores and clique identification. Journal of Mathematical Sociology, 2(1), 113–120.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Bornmann, L., & Daniel, H.-D. (2005). Does the h-index for ranking of scientists really work? Scientometrics, 65(3), 391–392.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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).

  • 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.

    Article  Google Scholar 

  • Cugmas, M., Ferligoj, A., & Kronegger, L. (2016). The stability of co-authorship structures. Scientometrics, 106(1), 163.

    Article  Google Scholar 

  • Dance, A. (2012). Authorship: Who’s on first? Nature, 489(7417), 591–593.

    Article  Google Scholar 

  • Danon, L., Diazguilera, A., Duch, J., & Arenas, A. (2005). Comparing community structure identification. Journal of Statistical Mechanics: Theory and Experiment, 2005(09), 09008.

    Article  Google Scholar 

  • De Haan, J. (1997). Authorship patterns in Dutch sociology. Scientometrics, 39(2), 197–208.

    Article  Google Scholar 

  • Garfield, E., & Merton, R. K. (1979). Citation indexing: Its theory and application in science, technology, and humanities (Vol. 8). New York: Wiley.

    Google Scholar 

  • 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.

    Article  MathSciNet  MATH  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Hagen, N. T. (2010). Harmonic publication and citation counting: Sharing authorship credit equitably—Not equally, geometrically or arithmetically. Scientometrics, 84(3), 785–793.

    Article  Google Scholar 

  • Hart, J. F. (1982). The highest form of the geographer’s art*. Annals of the Association of American Geographers, 72(1), 1–29.

    Article  Google Scholar 

  • 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.

    Article  MATH  Google Scholar 

  • Hummon, N. P., & Dereian, P. (1989). Connectivity in a citation network: The development of DNA theory*. Social Networks, 11(1), 39–63.

    Article  Google Scholar 

  • Kernighan, B. W., & Lin, S. (1970). An efficient heuristic procedure for partitioning graphs. Bell System Technical Journal, 49(2), 291–307.

    Article  MATH  Google Scholar 

  • Kronegger, L., Mali, F., Ferligoj, A., & Doreian, P. (2011). Collaboration structures in Slovenian scientific communities. Scientometrics, 90(2), 631–647.

    Article  Google Scholar 

  • Lee, S., & Bozeman, B. (2005). The impact of research collaboration on scientific productivity. Social Studies of Science, 35(5), 673–702.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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).

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Chapter  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Martin, G. J. (2005). All possible worlds: A history of geographical ideas. Oxford University Press. http://EconPapers.repec.org/RePEc:oxp:obooks:9780195168709.

  • 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.

    Chapter  Google Scholar 

  • Newman, M. E. J. (2006). Finding community structure in networks using the eigenvectors of matrices. Physical Review E, 74(3), 036104.

    Article  MathSciNet  Google Scholar 

  • Newman, M. E., & Girvan, M. (2004). Finding and evaluating community structure in networks. Physical Review E, 69(2), 026113.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  MathSciNet  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Wasserman, S., & Faust, K. (1994). Social network analysis: Methods and applications. Cambridge: Cambridge University Press.

    Book  MATH  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Chapter  Google Scholar 

  • Zhang, C., Bu, Y., & Ding, Y. (2016). Understanding scientific collaboration from the perspective of collaborators and their network structures. In IConference 2016 Proceedings.

Download references

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.

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Jie Zheng or Rui Li.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zheng, J., Gong, J., Li, R. et al. 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”. Scientometrics 113, 845–865 (2017). https://doi.org/10.1007/s11192-017-2515-7

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11192-017-2515-7

Keywords

Navigation