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Vector-valued impact measures and generation of specific indexes for research assessment

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Abstract

A mathematical structure for defining multi-valued bibliometric indices is provided with the aim of measuring the impact of general sources of information others than articles and journals—for example, repositories of datasets. The aim of the model is to use several scalar indices at the same time for giving a measure of the impact of a given source of information, that is, we construct vector valued indices. We use the properties of these vector valued indices in order to give a global answer to the problem of finding the optimal scalar index for measuring a particular aspect of the impact of an information source, depending on the criterion we want to fix for the evaluation of this impact. The main restrictions of our model are (1) it uses finite sets of scalar impact indices (altmetrics), and (2) these indices are assumed to be additive. The optimization procedure for finding the best tool for a fixed criterion is also presented. In particular, we show how to create an impact measure completely adapted to the policy of a specific research institution.

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References

  • Aleixandre Benavent, R., Valderrama Zurián, J. C., & González Alcaide, G. (2007). Scientific journals impact factor: Limitations and alternative indicators. El Profesional de la Información, 16(1), 4–11.

    Article  Google Scholar 

  • Alguliyev, R., Aliguliyev, R. & Ismayilova, N. (2015). Weighted impact factor (WIF) for assessing the quality of scientific journals. arXiv:1506.02783

  • Beauzamy, B. (1982). Introduction to Banach spaces and their geometry. Amsterdam: North-Holland.

    MATH  Google Scholar 

  • Beliakov, G., & James, S. (2011). Citation-based journal ranks: the use of fuzzy measures. Fuzzy Sets and Systems, 167, 101–119.

    Article  MathSciNet  MATH  Google Scholar 

  • Buela-Casal, G. (2003). Evaluating quality of articles and scientific journals. Proposal of weighted impact factor and a quality index. Psicothema, 15(1), 23–25.

    Google Scholar 

  • Diestel, J., & Uhl, J. J. (1977). Vector measures. Providence: Am. Math. Soc.

    Book  MATH  Google Scholar 

  • Dorta-González, P., & Dorta-González, M. I. (2013). Comparing journals from different fields of science and social science through a JCR subject categories normalized impact factor. Scientometrics, 95(2), 645–672.

    Article  Google Scholar 

  • Dorta-González, P., Dorta-González, M. I., Santos-Penate, D. R., & Suarez-Vega, R. (2014). Journal topic citation potential and between-field comparisons: The topic normalized impact factor. Journal of Informetrics, 8(2), 406–418.

    Article  Google Scholar 

  • Egghe, L., & Rousseau, R. (2002). A general frame-work for relative impact indicators. Canadian Journal of Information and Library Science, 27(1), 29–48.

    Google Scholar 

  • Ferrer-Sapena, A., Sánchez-Pérez, E. A., González, L. M., Peset, F. & Aleixandre-Benavent, R. (2016). The impact factor as a measuring tool of the prestige of the journals in research assessment in mathematics. Research Evaluation, 1–9. doi:10.1093/reseval/rvv041.

  • Ferrer-Sapena, A., Sánchez-Pérez, E. A., González, L. M., Peset, F., & Aleixandre-Benavent, R. (2015). Mathematical properties of weighted impact factors based on measures of prestige of the citing journals. Scientometrics, 105(3), 2089–2108.

    Article  Google Scholar 

  • Gagolewski, M., & Mesiar, R. (2014). Monotone measures and universal integrals in a uniform framework for the scientific impact assessment problem. Information Sciences, 263, 166–174.

    Article  MathSciNet  MATH  Google Scholar 

  • Habibzadeh, F., & Yadollahie, M. (2008). Journal weighted impact factor: A proposal. Journal of Informetrics, 2(2), 164–172.

    Article  Google Scholar 

  • Klement, E., Mesiar, R., & Pap, E. (2010). A universal integral as common frame for Choquet and Sugeno integral. IEEE Transactions on Fuzzy Systems, 18, 178–187.

    Article  Google Scholar 

  • Leydesdorff, L., & Opthof, T. (2010). Scopus’s source normalized impact per paper (SNIP) versus a journal impact factor based on fractional counting of citations. Journal of the American Society for Information Science and Technology, 61, 2365–2369.

    Article  Google Scholar 

  • Li, Y. R., Radicchi, F., Castellano, C., & Ruiz-Castillo, J. (2013). Quantitative evaluation of alternative field normalization procedures. Journal of Informetrics, 7(3), 746–755.

    Article  Google Scholar 

  • Moed, H. F. (2010). Measuring contextual citation impact of scientific journals. Journal of Informetrics, 4, 265–277.

    Article  Google Scholar 

  • Owlia, P., Vasei, M., Goliaei, B., & Nassiri, I. (2011). Normalized impact factor (NIF): An adjusted method for calculating the citation rate of biomedical journals. Journal of Biomedical Informatics, 44(2), 216–220.

    Article  Google Scholar 

  • Pinski, G., & Narin, F. (1976). Citation influence for journal aggregates of scientific publications: Theory, with application to the literature of physics. Information Processing and Management, 12, 297–312.

    Article  Google Scholar 

  • Piwowar, H. (2013). Altmetrics: Value all research products. Nature, 493(7431), 159–159.

    Google Scholar 

  • Pudovkin,A.I., & Garfield, E. (2004). Rank-normalized impact factor: A way to compare journal performance across subject categories. In Proceedings of the 67th annual meeting of the American Society for Information science and Technology, 41, 507-515.

  • Rousseau, R. (2002). Journal evaluation: Technical and practical issues. Library Trends, 50(3), 418–439.

    Google Scholar 

  • Ruiz Castillo, J., & Waltman, L. (2015). Field-normalized citation impact indicators using algorithmically constructed classification systems of science. Journal of Informetrics, 9, 102–117.

    Article  Google Scholar 

  • Torra, V., & Narukawa, Y. (2008). The h-index and the number of citations: Two fuzzy integrals. IEEE Transactions on Fuzzy Systems, 16, 795–797.

    Article  MathSciNet  Google Scholar 

  • Waltman, L., & van Eck, N. J. (2008). Some comments on the journal weighted impact factor proposed by Habibzadeh and Yadollahie. Journal of Informetrics, 2(4), 369–372.

    Article  Google Scholar 

  • Waltman, L., & van Eck, N. J. (2010). The relation between Eigenfactor, audience factor, and influence weight. Journal of the American Society for Information Science and Technology, 61, 1476–1486.

    Article  Google Scholar 

  • Zahedi, Z., Costas, R., & Wouters, P. (2014). How well developed are altmetrics? A cross-disciplinary analysis of the presence of ’alternative metrics’ in scientific publications. Scientometrics, 101(2), 1491–1513.

    Article  Google Scholar 

  • Zitt, M. (2010). Citing-side normalization of journal impact: A robust variant of the Audience Factor. Journal of Informetrics, 4(3), 392–406.

    Article  Google Scholar 

  • Zitt, M. (2011). Behind citing-side normalization of citations: Some properties of the journal impact factor. Scientometrics, 89, 329–344.

    Article  Google Scholar 

  • Zitt, M., & Small, H. (2008). Modifying the journal impact factor by fractional citation weighting: The audience factor. Journal of the American Society for Information Science and Technology, 59, 1856–1860.

    Article  Google Scholar 

  • Zyczkowski, K. (2010). Citation graph, weighted impact factors and performance indices. Scientometrics, 85(1), 301–315.

    Article  Google Scholar 

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Acknowledgments

The authors would like to thank the referees for carefully reading of the manuscript and giving many helpful suggestions.

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Correspondence to E. A. Sánchez-Pérez.

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Calabuig, J.M., Ferrer-Sapena, A. & Sánchez-Pérez, E.A. Vector-valued impact measures and generation of specific indexes for research assessment. Scientometrics 108, 1425–1443 (2016). https://doi.org/10.1007/s11192-016-2039-6

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  • DOI: https://doi.org/10.1007/s11192-016-2039-6

Keywords

Mathematics Subject Classification

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