Skip to main content
SpringerLink
Log in

Research collaboration networks of two OIC nations: comparative study between Turkey and Malaysia in the field of ‘Energy Fuels’, 2009–2011

  • Published:
Scientometrics Aims and scope Submit manuscript

Abstract

With the world in the midst of an energy crisis, recent research has placed considerable emphasis on harnessing renewable and sustainable energy while efficiently using fossil fuels. Researchers create and sustain academic societies as a result of social interactions. This study takes a social network perspective to understand researchers’ associations using two Organisation of Islamic Co-operation nations, Turkey and Malaysia, in the fast-developing field of ‘Energy Fuels’. The study found both similarities and differences in the scholarly networks of these two countries. The mean distance between the authors in the Turkey and Malaysia networks was 8.4 and 6.5, respectively, confirming the small world nature of these networks. The popularity, position, and prestige of the authors in the network, as determined through centrality measures, had a statistically significant effect on research performance. These measures, however, were far more correlated with the research performance of the authors in the Malaysia network than in the Turkey network. PageRank centrality was found to be the most efficient topological measure when it came to correlation with research performance. We used authors’ ‘degree’ to reach to the ‘core’ (‘Deg-Core’) of the network (in contrast to the K-Core method), which was found to capture more productive authors. A method to detect academic communities of productive authors by extracting motifs (large cliques) from the network is suggested. Finally, we visualize the cognitive structure of both countries using a 2-mode network representing research focus areas (RFAs) and prominent authors working in these RFAs.

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

Access this article

Log in via an institution

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

Similar content being viewed by others

References

  • Abbasi, A., Altmann, J., & Hossain, L. (2011). Identifying the effects of co-authorship networks on the performance of scholars: A correlation and regression analysis of performance measures and social network analysis measures. Journal of Informetrics, 5(4), 594–607.

    Article  Google Scholar 

  • Abbasi, A., Hossain, L., & Leydesdorff, L. (2012). Betweenness centrality as a driver of preferential attachment in the evolution of research collaboration networks. Journal of Informetrics, 6(3), 403–412. doi:10.1016/j.joi.2012.01.002.

    Article  Google Scholar 

  • Abramo, G., D’Angelo, C. A., & Cicero, T. (2012). What is the appropriate length of the publication period over which to assess research performance? Scientometrics, 93(3), 1005–1017. doi:10.1007/s11192-012-0714-9.

    Article  Google Scholar 

  • Abrizah, A., & Wee, M. C. (2011). Malaysia’s computer science research productivity based on publications in the Web of Science, 2000–2010. Malaysian Journal of Library & Information Science, 16(1), 109–124.

    Google Scholar 

  • Asif, M., & Muneer, T. (2007). Energy supply, its demand and security issues for developed and emerging economies. Renewable and Sustainable Energy Reviews, 11(7), 1388–1413.

    Article  Google Scholar 

  • Barabasi, A. L., & Albert, R. (1999). Emergence of scaling in random networks. Science, 286(5439), 509–512.

    Article  MathSciNet  Google Scholar 

  • Barabasi, A. L., Jeong, H., Neda, Z., Ravasz, E., Schubert, A., & Vicsek, T. (2002). Evolution of the social network of scientific collaborations. Physica A: Statistical Mechanics and Its Applications, 311(3–4), 590–614.

    Article  MATH  MathSciNet  Google Scholar 

  • Beaver, D. D. (2001). Reflections on scientific collaboration, (and its study): past, present, and future. Scientometrics, 52(3), 365–377.

    Article  Google Scholar 

  • Bilgili, M., & Simsek, E. (2012). Wind energy potential and turbine installations in Turkey. Energy Sources, Part B: Economics, Planning and Policy, 7(2), 140–151.

    Article  Google Scholar 

  • Borgatti, S. P. (2009). 2-Mode concepts in social network analysis. Encyclopedia of Complexity and System Science, 8279–8291.

  • Boyack, K. W., Klavans, R., & Börner, K. (2005). Mapping the backbone of science. Scientometrics, 64(3), 351–374.

    Article  Google Scholar 

  • Clauset, A., Newman, M. E. J., & Moore, C. (2004). Finding community structure in very large networks. Physical Review E, 70(6), 066111.

    Article  Google Scholar 

  • Crane, D. (1972). Invisible colleges: Diffusion of knowledge in scientific communities. Chicago, IL: University of Chicago Press.

    Google Scholar 

  • de Price, D. J. S., & Beaver, D. (1966). Collaboration in an invisible college. American Psychologist, 21(11), 1011.

    Article  Google Scholar 

  • Dong, B. S., Xu, G. Q., Luo, X., Cai, Y., & Gao, W. (2012). A bibliometric analysis of solar power research from 1991 to 2010. Scientometrics, 93(3), 1101–1117. doi:10.1007/s11192-012-0730-9.

    Article  Google Scholar 

  • Dresselhaus, M., & Thomas, I. (2001). Alternative energy technologies. Nature, 414(6861), 332–337.

    Article  Google Scholar 

  • Fatt, C. K., Ujum, E. A., & Ratnavelu, K. (2010). The structure of collaboration in the journal of finance. Scientometrics, 85(3), 849–860. doi:10.1007/s11192-010-0254-0.

    Google Scholar 

  • Faust, K. (1997). Centrality in affiliation networks. Social Networks, 19(2), 157–191. doi:10.1016/s0378-8733(96)00300-0.

    Article  Google Scholar 

  • Garfield, E. (1969). British quest for uniqueness versus American egocentrism. Nature, 223, 763.

    Article  Google Scholar 

  • Gerke, S., & Evers, H.-D. (2006). Globalizing local knowledge: Social science research on Southeast Asia, 1970–2000. SOJOURN: Journal of Social Issues in Southeast Asia, 21(1), 1–21.

    Article  Google Scholar 

  • Girvan, M., & Newman, M. E. J. (2002). Community structure in social and biological networks. Proceedings of the National Academy of Sciences of the United States of America, 99(12), 7821–7826. doi:10.1073/pnas.122653799.

    Article  MATH  MathSciNet  Google Scholar 

  • Glänzel, W., & Schubert, A. (2005). Analysing scientific networks through co-authorship. In Handbook of quantitative science and technology research (pp. 257–276). Dordrecht, The Netherlands: Kluwer Academic Publishers.

  • Glänzel, W., & Thijs, B. (2011). Using ‘core documents’ for the representation of clusters and topics. Scientometrics, 88(1), 297–309.

    Article  Google Scholar 

  • Hanneman, R. A., & Riddle, M. (2005). Introduction to social network methods. Riverside: University of California.

    Google Scholar 

  • Hassan, E. (2005). The evolution of the knowledge structure of fuel cells. Scientometrics, 62(2), 223–238. doi:10.1007/s11192-005-0016-6.

    Article  Google Scholar 

  • Hassan, S. U., & Haddawy, P. (2013). Measuring international knowledge flows and scholarly impact of scientific research. Scientometrics, 94(1), 163–179. doi:10.1007/s11192-012-0786-6.

    Article  Google Scholar 

  • Hou, H., Kretschmer, H., & Liu, Z. (2008). The structure of scientific collaboration networks in scientometrics. Scientometrics, 75(2), 189–202. doi:10.1007/s11192-007-1771-3.

    Article  Google Scholar 

  • Huang, M. H., Dong, H. R., & Chen, D. Z. (2013). The unbalanced performance and regional differences in scientific and technological collaboration in the field of solar cells. Scientometrics, 94(1), 423–438. doi:10.1007/s11192-012-0755-0.

    Article  Google Scholar 

  • Jang, S.-L., Chen, L.-J., Chen, J. H., & Chiu, Y.-C. (2013). Innovation and production in the global solar photovoltaic industry. Scientometrics, 94(3), 1021–1036.

    Article  Google Scholar 

  • Katz, J. S., & Martin, B. R. (1997). What is research collaboration?. Research Policy, 26(1), 1–18.

    Article  Google Scholar 

  • Kosslyn, S. M. (2006). Graph design for the eye and mind. New York, USA: Oxford University Press.

    Book  Google Scholar 

  • Kronegger, L., Mali, F., Ferligoj, A., & Doreian, P. (2012). Collaboration structures in Slovenian scientific communities. Scientometrics, 90(2), 631–647. doi:10.1007/s11192-011-0493-8.

    Article  Google Scholar 

  • Kumar, S. (2011). Analyzing social media networks with NodeXL: Insights from a connected world. Information Research: An International Electronic Journal, 16(2).

  • Kumar, S., & Jan, J. M. (2013). Mapping research collaborations in the business and management field in Malaysia, 1980–2010. Scientometrics, 1–27, doi:10.1007/s11192-013-0994-8.

  • Lee, D. H., Seo, I. W., Choe, H. C., & Kim, H. D. (2012). Collaboration network patterns and research performance: The case of Korean public research institutions. Scientometrics, 91(3), 925–942. doi:10.1007/s11192-011-0602-8.

    Article  Google Scholar 

  • Lewison, G., & Markusova, V. (2010). The evaluation of Russian cancer research. Research Evaluation, 19(2), 129–144. doi:10.3152/095820210x510098.

    Article  Google Scholar 

  • Linton, C. F. (1977). A set of measures of centrality based on betweenness. Sociometry, 40(1), 35–41.

    Article  MathSciNet  Google Scholar 

  • Liu, X. M., 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. doi:10.1016/j.ipm.2005.03.012.

    Article  Google Scholar 

  • Lotka, A. J. (1926). The frequency distribution of scientific productivity. Journal of Washington Academy Sciences, 16(12), 317–323.

    Google Scholar 

  • Luukkonen, T., Persson, O., & Sivertsen, G. (1992). Understanding patterns of international scientific collaboration. Science, Technology and Human Values, 17(1), 101–126.

    Article  Google Scholar 

  • Mane, K. K., & Börner, K. (2004). Mapping topics and topic bursts in PNAS. Proceedings of the National Academy of Sciences of the United States of America, 101(Suppl 1), 5287.

    Article  Google Scholar 

  • McKendry, P. (2002). Energy production from biomass (part 1): Overview of biomass. Bioresource Technology, 83(1), 37–46.

    Article  Google Scholar 

  • Melin, G., & Persson, O. (1996). Studying research collaboration using co-authorships. Scientometrics, 36(3), 363–377.

    Article  Google Scholar 

  • Milo, R., Shen-Orr, S., Itzkovitz, S., Kashtan, N., Chklovskii, D., & Alon, U. (2002). Network motifs: Simple building blocks of complex networks. Science Signaling, 298(5594), 824.

    Google Scholar 

  • Milojević, S., Sugimoto, C. R., Yan, E., & Ding, Y. (2011). The cognitive structure of library and information science: Analysis of article title words. Journal of the American Society for Information Science and Technology, 62(10), 1933–1953.

    Article  Google Scholar 

  • Moody, J. (2004). The structure of a social science collaboration network: Disciplinary cohesion from 1963 to 1999. American Sociological Review, 69(2), 213–238.

    Article  Google Scholar 

  • Newman, M. E. J. (2001a). Scientific collaboration networks. I. Network construction and fundamental results. Physical Review E, 64(1), 016131.

    Article  Google Scholar 

  • Newman, M. E. J. (2001b). Scientific collaboration networks. II. Shortest paths, weighted networks, and centrality. Physical Review E, 64(1), 016132.

    Article  Google Scholar 

  • Newman, M. E. J. (2001c). The structure of scientific collaboration networks. Proceedings of the National Academy of Sciences of the United States of America, 98(2), 404–409.

    Article  MATH  MathSciNet  Google Scholar 

  • Newman, M. E. J. (2004). Coauthorship networks and patterns of scientific collaboration. Proceedings of the National Academy of Sciences of the United States of America, 101, 5200–5205. doi:10.1073/pnas.0307545100.

    Article  Google Scholar 

  • Newman, M. E. J. (2007). The mathematics of networks. In The new palgrave encyclopedia of economics. New York: Palgrave MacMillan.

  • Otte, E., & Rousseau, R. (2002). Social network analysis: A powerful strategy, also for the information sciences. Journal of Information Science, 28(6), 441–453.

    Article  Google Scholar 

  • Ozel, B. (2012). Collaboration structure and knowledge diffusion in Turkish management academia. Scientometrics, 93(1), 183–206. doi:10.1007/s11192-012-0641-9.

    Article  MathSciNet  Google Scholar 

  • Page, L., Brin, S., Motwani, R., & Winograd, T. (1999). The PageRank citation ranking: Bringing order to the web. Stanford: Stanford University InfoLab.

    Google Scholar 

  • Poole, A. D., Bain, R. L., Cavallo, A., Larson, E. D., Macedo, I. C., Barnett, A. M., et al. (1992). Renewable energy: Sources for fuels and electricity. Washington, D.C.: Island Press.

    Google Scholar 

  • Price, D. S. (1963). Big science, little science. New York: Columbia University.

    Google Scholar 

  • Quatman, C., & Chelladurai, P. (2008). The social construction of knowledge in the field of sport management: A social network perspective. Journal of Sport Management, 22(6), 651–676.

    Google Scholar 

  • Racherla, P., & Hu, C. (2010). A social network perspective of tourism research collaborations. Annals of Tourism Research, 37(4), 1012–1034. doi:10.1016/j.annals.2010.03.008.

    Article  Google Scholar 

  • Rostow, W. W. (1991). The stages of economic growth: A non-communist manifesto. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • Rousseau, B., & Rousseau, R. (2000). LOTKA: A program to fit a power law distribution to observed frequency data. Cybermetrics: International Journal of Scientometrics, Informetrics and Bibliometrics, 4(1), 4.

    Google Scholar 

  • Sakata, I., Sasaki, H., & Inoue, T. (2011). Structure of international research collaboration in wind and solar energy. In 2011 IEEE international conference on industrial engineering and engineering management (IEEM) (pp. 1053–1057). New York: IEEE.

  • Sanz-Casado, E., Garcia-Zorita, J. C., Serrano-López, A. E., Larsen, B., & Ingwersen, P. (2012). Renewable energy research 1995–2009: A case study of wind power research in EU, Spain, Germany and Denmark. Scientometrics, 1–28. doi:10.1007/s11192-012-0825-3.

  • Sci2, T. (2009). Science of science (Sci 2 ) tool. Indiana University and SciTech Strategies. http://sci.slis.indiana.edu.

  • Series, O. O. (2012). Current stance of energy resources and potential in OIC member countries.

  • SESRIC, T. (2010). Research and scientific development in OIC countries.

  • Smalheiser, N. R., & Torvik, V. I. (2009). Author name disambiguation. Annual Review of Information Science and Technology, 43(1), 1–43.

    Article  Google Scholar 

  • Smith, M. A., Shneiderman, B., Milic-Frayling, N., Rodrigues, E. M., Barash, V., Dunne, C., et al. (2011). Analyzing (social media) networks with NodeXL. In Proceedings on communities and technologies 2009 (pp. 255–264). New York: ACM.

  • Sopian, K., Ali, B., & Asim, N. (2011). Strategies for renewable energy applications in the organization of Islamic conference (OIC) countries. Renewable and Sustainable Energy Reviews, 15(9), 4706–4725.

    Article  Google Scholar 

  • Talukdar, D. (2011). Patterns of research productivity in the business ethics literature: Insights from analyses of bibliometric distributions. Journal of Business Ethics, 98(1), 137–151.

    Article  Google Scholar 

  • Tang, L., & Walsh, J. P. (2010). Bibliometric fingerprints: Name disambiguation based on approximate structure equivalence of cognitive maps. Scientometrics, 84(3), 763–784. doi:10.1007/s11192-010-0196-6.

    Article  Google Scholar 

  • Thomas, S. M. (1992). The evaluation of plant biomass research: A case-study of the problems inherent in bibliometric indicators. Scientometrics, 23(1), 149–167. doi:10.1007/bf02020920.

    Article  Google Scholar 

  • Tsay, M. Y. (2008). A bibliometric analysis of hydrogen energy literature, 1965–2005. Scientometrics, 75(3), 421–438. doi:10.1007/s11192-007-1785-x.

    Article  Google Scholar 

  • Uddin, S., Hossain, L., Abbasi, A., & Rasmussen, K. (2012). Trend and efficiency analysis of co-authorship network. Scientometrics, 90(2), 687–699. doi:10.1007/s11192-011-0511-x.

    Article  Google Scholar 

  • Vidican, G., Woon, W. L., & Madnick, S. (2009). Measuring innovation using bibliometric techniques: The case of solar photovoltaic industry. Sloan Working Papers.

  • Wasserman, S., & Faust, K. (1994). Social network analysis, methods and applications. In Structural analysis in the social sciences (1st ed.). Cambridge: Cambridge University Press.

  • Watts, D. J., & Strogatz, S. H. (1998). Collective dynamics of ‘small-world’ networks. Nature, 393(6684), 440–442.

    Article  Google Scholar 

  • Yan, E. J., & 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. doi:10.1002/asi.21128.

    Article  Google Scholar 

  • Yan, E. J., Ding, Y., & Zhu, Q. H. (2010). Mapping library and information science in China: A coauthorship network analysis. Scientometrics, 83(1), 115–131. doi:10.1007/s11192-009-0027-9.

    Article  Google Scholar 

  • Yin, L. C., Kretschmer, H., Hanneman, R. A., & Liu, Z. Y. (2006). Connection and stratification in research collaboration: An analysis of the COLLNET network. Information Processing and Management, 42(6), 1599–1613. doi:10.1016/j.ipm.2006.03.021.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Asia–Europe Institute, University of Malaya, 50603, Kuala Lumpur, Malaysia

    Sameer Kumar

  2. Faculty of Languages and Linguistics, University of Malaya, 50603, Kuala Lumpur, Malaysia

    Jariah Mohd. Jan

Authors
  1. Sameer Kumar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jariah Mohd. Jan
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sameer Kumar.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Kumar, S., Jan, J.M. Research collaboration networks of two OIC nations: comparative study between Turkey and Malaysia in the field of ‘Energy Fuels’, 2009–2011. Scientometrics 98, 387–414 (2014). https://doi.org/10.1007/s11192-013-1059-8

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11192-013-1059-8

Keywords

Search

Navigation