Co-word based thematic analysis of renewable energy (1990–2010)
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This article describes an analysis of keywords which was aimed at revealing publication patterns in the field of renewable energy, including the temporal evolution of its different research lines over the last two decades. To this end, we first retrieved the records of the sample, then we processed the keywords to resolve their obvious problems of synonymy and to limit the study to those most used. The final results showed a clear increase in scientific production related to alternative energies, and a structure corresponding to five major clusters which, at a finer level of resolution, were decomposed into 22. We analyzed the structure of the clusters and their temporal evolution, paying particular attention to uncovering the bursty periods of the different lines of research.
KeywordsBibliometrics Co-word analysis Renewable energy Clustering
This work was financed by the Junta de Extremadura—Consejería de Educación Ciencia & Tecnología and the Fondo Social Europeo as part of predoctoral studentship PRE07051 and the research group grant GR10019, and by the Plan Nacional de Investigación Científica, Desarrollo e Innovación Tecnológica 2008-2011 and the Fondo Europeo de Desarrollo Regional (FEDER) as part of research projects TIN2008-06514-C02-01 and TIN2008-06514-C02-02.
- Callon, M., Courtial, J. P., & Penan, H. (1995). Cienciometría. El estudio cuantitativo de la actividad científica: de la bibliometría a la vigencia tecnológica. Gijón: Ediciones TREA.Google Scholar
- Chen, Y. H., Chen, C. Y., & Lee, S. C. (2010). Technology forecasting of new clean energy: the example of hydrogen energy and fuel cell. African Journal of Business Management, 4(7), 1372–1380.Google Scholar
- Corera Álvarez, E., & Moya-Anegón, F. (2009). Chemistry in Spain: bibliometric analysis through Scopus. Chemistry Today, 27(6), 61–64.Google Scholar
- Hane, P. (2004). Elsevier announces Scopus service. Information today, http://newsbreaks.infotoday.com/nbreader.asp?ArticleID=16494. Accessed 9 June 2011.
- Kleinberg, J. (2002). Bursty and hierarchical structure in streams, Proceedings of the 8th ACM SIGKDD international conference on knowledge discovery and data mining (pp. 91–101). New York: ACM.Google Scholar
- Kleinberg, J. (2004). Temporal dynamics of on-line information streams. In M. Garofalakis, J. Gehrke, & R. Rastogi (Eds.), Data stream management: processing high-speed data streams. Berlin: Springer.Google Scholar
- Leydesdorff, L., Moya Anegón, F., & Guerrero Bote, V. P. (2010). Journal maps on the basis of Scopus data: a comparison with the journal citation reports of the ISI. Journal of the American Society for Information Science and Technology, 61(2), 352–369.Google Scholar
- Pickering, B. (2004). Elsevier prepares Scopus to rival ISI Web of science, Information world review. Amsterdam: Elsevier.Google Scholar
- Romo-Fernández, L. M., Guerrero-Bote, V. P., Moya-Anegón, F. (2012). World scientific production on renewable energy, sustainability and the environment. Energy for Sustainable Development, 16, 500–508.Google Scholar
- Woon, W. L., Henschel, A. & Madnick, S. (2009). A framework for technology forecasting and visualization. 2009 International conference on innovations in information technology, IIT ‘09, pp 155–159.Google Scholar