This work is licensed under the Creative Commons Attribution 4.0 International License.
Abramo, G. (2018). Revisiting the scientometric conceptualization of impact and its measurement. Journal of Informetrics, 12(3), 590–597.AbramoG. (2018). Revisiting the scientometric conceptualization of impact and its measurement. Journal of Informetrics, 12(3), 590–597.Search in Google Scholar
Aithal, P. S. & Aithal, S. (2023). Key performance indicators (kpi) for researchers at different levels & strategies to achieve it. International Journal of Management, Technology and Social Sciences (IJMTS), 8(3), 294–325.AithalP. S.AithalS. (2023). Key performance indicators (kpi) for researchers at different levels & strategies to achieve it. International Journal of Management, Technology and Social Sciences (IJMTS), 8(3), 294–325.Search in Google Scholar
Alexi, A., Lazebnik, T., & Rosenfeld, A. (2024). The scientometrics and reciprocality underlying co-authorship panels in google scholar profiles. Scientometrics, 129(6), 3303–3313.AlexiA.LazebnikT.RosenfeldA. (2024). The scientometrics and reciprocality underlying co-authorship panels in google scholar profiles. Scientometrics, 129(6), 3303–3313.Search in Google Scholar
Andersen, J. P., Didegah, F., and Schneider, J. W. (2017). The necessity of comparing like with like in evaluative scientometrics: A first attempt to produce and test a generic approach to identifying relevant benchmark units. In STI Conference Paris: Open indicators: innovation, participation and actor-based STI indicators.AndersenJ. P.DidegahF.SchneiderJ. W. (2017). The necessity of comparing like with like in evaluative scientometrics: A first attempt to produce and test a generic approach to identifying relevant benchmark units. In STI Conference Paris: Open indicators: innovation, participation and actor-based STI indicators.Search in Google Scholar
Ansari, M., Noruzi, A., Fallah, M., Saedmoucheshi, S., & Valinejadi, A. (2022). Bibliometric Analysis of the Top Ten Percent Iranian Medical Researchers Based on the I10-index and the H-index in Web of Science. Informology, 1(2), 27-40.AnsariM.NoruziA.FallahM.SaedmoucheshiS.ValinejadiA. (2022). Bibliometric Analysis of the Top Ten Percent Iranian Medical Researchers Based on the I10-index and the H-index in Web of Science. Informology, 1(2), 27-40.Search in Google Scholar
Aviv-Reuven, S. & Rosenfeld, A. (2023). A logical set theory approach to journal subject classification analysis: intra-system irregularities and inter-system discrepancies in web of science and scopus. Scientometrics, 128(1), 157–175.Aviv-ReuvenSRosenfeldA. (2023). A logical set theory approach to journal subject classification analysis: intra-system irregularities and inter-system discrepancies in web of science and scopus. Scientometrics, 128(1), 157–175.Search in Google Scholar
Bai, X., Zhang, F., & Lee, I. (2019). Predicting the citations of scholarly paper. Journal of Informetrics, 13(1), 407–418.BaiX.ZhangF.LeeI. (2019). Predicting the citations of scholarly paper. Journal of Informetrics, 13(1), 407–418.Search in Google Scholar
Ball, P. (2007). Achievement index climbs the ranks. NATURE-LONDON-, 448(7155), 737.BallP. (2007). Achievement index climbs the ranks. NATURE-LONDON-, 448(7155), 737.Search in Google Scholar
Bar-Ilan, J. & Halevi, G. (2017). Post retraction citations in context: a case study. Scientometrics, 113(1), 547–565.Bar-IlanJHaleviG. (2017). Post retraction citations in context: a case study. Scientometrics, 113(1), 547–565.Search in Google Scholar
Biryukov, M., & Dong, C. (2010). Analysis of computer science communities based on DBLP. In Research and Advanced Technology for Digital Libraries: 14th European Conference, ECDL 2010, Glasgow, UK, September 6-10, 2010. Proceedings 14 (pp. 228-235). Springer Berlin Heidelberg.BiryukovM.DongC. (2010). Analysis of computer science communities based on DBLP. In Research and Advanced Technology for Digital Libraries: 14th European Conference, ECDL 2010, Glasgow, UK, September6-10, 2010. Proceedings 14 (pp. 228-235). Springer Berlin Heidelberg.Search in Google Scholar
Borchardt, R. & Hartings, M. R. (2018). The academic papers researchers regard as significant are not those that are highly cited. Impact of Social Sciences Blog.BorchardtR.HartingsM. R. (2018). The academic papers researchers regard as significant are not those that are highly cited. Impact of Social Sciences Blog.Search in Google Scholar
Cavacini, A. (2015). What is the best database for computer science journal articles? Scientometrics, 102, 2059– 2071.CavaciniA. (2015). What is the best database for computer science journal articles? Scientometrics, 102, 2059– 2071.Search in Google Scholar
Dillon, R. (2022). The u-index: a simple metric to objectively measure academic impact of individual researchers. arXiv preprint arXiv:2205.14925.DillonR. (2022). The u-index: a simple metric to objectively measure academic impact of individual researchers. arXiv preprint arXiv:2205.14925.Search in Google Scholar
Egghe, L. (2006). Theory and practise of the g-index. Scientometrics, 69(1), 131–152.EggheL. (2006). Theory and practise of the g-index. Scientometrics, 69(1), 131–152.Search in Google Scholar
Froghi, S., Ahmed, K., Finch, A., Fitzpatrick, J. M., Khan, M. S., & Dasgupta, P. (2012). Indicators for research performance evaluation: An overview. BJU International-British Journal of Urology, 109(3), 321.FroghiS.AhmedK.FinchA.FitzpatrickJ. M.KhanM. S.DasguptaP. (2012). Indicators for research performance evaluation: An overview. BJU International-British Journal of Urology, 109(3), 321.Search in Google Scholar
Garfield, E. (1999). Journal impact factor: a brief review. Cmaj, 161(8), 979–980.GarfieldE. (1999). Journal impact factor: a brief review. Cmaj, 161(8), 979–980.Search in Google Scholar
Garousi, V. & Fernandes, J. M. (2016). Highly-cited papers in software engineering: The top-100. Information and Software Technology, 71, 108–128.GarousiV.FernandesJ. M. (2016). Highly-cited papers in software engineering: The top-100. Information and Software Technology, 71, 108–128.Search in Google Scholar
Glänzel, W. & Schoepflin, U. (1994). Little scientometrics, big scientometrics… and beyond? Scientometrics, 30, 375–384.GlänzelW.SchoepflinU. (1994). Little scientometrics, big scientometrics… and beyond? Scientometrics, 30, 375–384.Search in Google Scholar
Gusenbauer, M. (2019). Google scholar to overshadow them all? comparing the sizes of 12 academic search engines and bibliographic databases. Scientometrics, 118(1), 177–214.GusenbauerM. (2019). Google scholar to overshadow them all? comparing the sizes of 12 academic search engines and bibliographic databases. Scientometrics, 118(1), 177–214.Search in Google Scholar
Hernández, J. M. & Dorta-González, P. (2020). Interdisciplinarity metric based on the co-citation network. Mathematics, 8(4), 544.HernándezJ. M.Dorta-GonzálezP (2020). Interdisciplinarity metric based on the co-citation network. Mathematics, 8(4), 544.Search in Google Scholar
Hu, Y., Hu, C., Tran, T., Kasturi, T., Joseph, E., & Gillingham, M. (2021). What’s in a name?–gender classification of names with character based machine learning models. Data Mining and Knowledge Discovery, 35(4), 1537-1563.HuY.HuC.TranT.KasturiT.JosephE.GillinghamM. (2021). What’s in a name?–gender classification of names with character based machine learning models. Data Mining and Knowledge Discovery, 35(4), 1537-1563.Search in Google Scholar
Jong, L., Franssen, T., and Pinfield, S. (2021). ‘excellence’in the research ecosystem: a literature review. RoRI Working Paper Series, 5(5).JongL.FranssenT.PinfieldS. (2021). ‘excellence’in the research ecosystem: a literature review. RoRI Working Paper Series, 5(5).Search in Google Scholar
Ke, Q., Ferrara, E., Radicchi, F., and Flammini, A. (2015). Defining and identifying sleeping beauties in science. Proceedings of the National Academy of Sciences, 112(24), 7426–7431.KeQ.FerraraE.RadicchiF.FlamminiA. (2015). Defining and identifying sleeping beauties in science. Proceedings of the National Academy of Sciences, 112(24), 7426–7431.Search in Google Scholar
Kim, J. (2018). Evaluating author name disambiguation for digital libraries: a case of dblp. Scientometrics, 116, 1867–1886.KimJ. (2018). Evaluating author name disambiguation for digital libraries: a case of dblp. Scientometrics, 116, 1867–1886.Search in Google Scholar
Kim, J. (2019). Correction to: Evaluating author name disambiguation for digital libraries: a case of dblp. Scientometrics, 118, 383–383.KimJ. (2019). Correction to: Evaluating author name disambiguation for digital libraries: a case of dblp. Scientometrics, 118, 383–383.Search in Google Scholar
Koltun, V. & Hafner, D. (2021). The h-index is no longer an effective correlate of scientific reputation. PLoS One, 16(6): e0253397.KoltunV.HafnerD. (2021). The h-index is no longer an effective correlate of scientific reputation. PLoS One, 16(6): e0253397.Search in Google Scholar
Kozak, M. & Bornmann, L. (2012). A new family of cumulative indexes for measuring scientific performance. PloS one, 7(10): e47679.KozakM.BornmannL. (2012). A new family of cumulative indexes for measuring scientific performance. PloS one, 7(10): e47679.Search in Google Scholar
Kpolovie, P. J., Onoshagbegbe, E. S.(2017). Research productivity: h-index and i10-index of academics in nigerian universities. International Journal of Quantitative and Qualitative Research Methods, 5(2), 62–123.KpolovieP. J.OnoshagbegbeE. S.(2017). Research productivity: h-index and i10-index of academics in nigerian universities. International Journal of Quantitative and Qualitative Research Methods, 5(2), 62–123.Search in Google Scholar
Kulczycki, E., Korzen’, M., & Korytkowski, P. (2017). Toward an excellence-based research funding system: Evidence from poland. Journal of Informetrics, 11(1), 282–298.KulczyckiE.Korzen’M.KorytkowskiP. (2017). Toward an excellence-based research funding system: Evidence from poland. Journal of Informetrics, 11(1), 282–298.Search in Google Scholar
Kumar, D., Bhowmick, P. K., & Paik, J. (2023). Researcher influence prediction (resip) using academic genealogy network. Journal of Informetrics, 17(2), 101392.KumarD.BhowmickP. K.PaikJ. (2023). Researcher influence prediction (resip) using academic genealogy network. Journal of Informetrics, 17(2), 101392.Search in Google Scholar
Kusakunniran, W., Ponn, T., Boonsom, N., Wahakit, S., & Thongkanchorn, K. (2021). Construction of h5-index for conference ranking indicator and its correlation to era. Journal of Information & Knowledge Management, 20(01):2150011.KusakunniranW.PonnT.BoonsomN.WahakitS.ThongkanchornK. (2021). Construction of h5-index for conference ranking indicator and its correlation to era. Journal of Information & Knowledge Management, 20(01):2150011.Search in Google Scholar
Leibel, C. & Bornmann, L. (2024). What do we know about the disruption index in scientometrics? an overview of the literature. Scientometrics, 129(1), 601–639.LeibelC.BornmannL. (2024). What do we know about the disruption index in scientometrics? an overview of the literature. Scientometrics, 129(1), 601–639.Search in Google Scholar
Lindahl, J. (2023). Conscientiousness predicts doctoral students’ research productivity. Journal of Informetrics, 17(1):101353.LindahlJ. (2023). Conscientiousness predicts doctoral students’ research productivity. Journal of Informetrics, 17(1):101353.Search in Google Scholar
Lippi, G. & Mattiuzzi, C. (2017). Scientist impact factor (sif): a new metric for improving scientists’ evaluation? Annals of Translational Medicine, 5(15).LippiG.MattiuzziC. (2017). Scientist impact factor (sif): a new metric for improving scientists’ evaluation? Annals of Translational Medicine, 5(15).Search in Google Scholar
Liu, Y., Jiang, M., Hu, L., & He, Z. (2023). The statistical nature of h-index of a network node and its extensions. Journal of Informetrics, 17(3):101424.LiuY.JiangM.HuL.HeZ. (2023). The statistical nature of h-index of a network node and its extensions. Journal of Informetrics, 17(3):101424.Search in Google Scholar
MacFarland, T. W., Yates, J. M., MacFarland, T. W., & Yates, J. M. (2016). Mann–whitney u test. Introduction to nonparametric statistics for the biological sciences using R, 103-132.MacFarlandT. W.YatesJ. M.MacFarlandT. W.YatesJ. M. (2016). Mann–whitney u test. Introduction to nonparametric statistics for the biological sciences using R, 103-132.Search in Google Scholar
Massucci, F. A. & Docampo, D. (2019). Measuring the academic reputation through citation networks via pagerank. Journal of Informetrics, 13(1), 185–201.MassucciF. A.DocampoD. (2019). Measuring the academic reputation through citation networks via pagerank. Journal of Informetrics, 13(1), 185–201.Search in Google Scholar
Mavrogenis, A. F., Pećina, M., Chen, W., & Scarlat, M. M. (2020). Useful and useless publications measured by bibliometrics and scientometrics in orthopaedic surgery. Are the relevance of a journal and publication metrics useful enough for the scientific promotion of surgeons?. International Orthopaedics, 44, 1875–1879.MavrogenisA. F.PećinaM.ChenW.ScarlatM. M. (2020). Useful and useless publications measured by bibliometrics and scientometrics in orthopaedic surgery. Are the relevance of a journal and publication metrics useful enough for the scientific promotion of surgeons?. International Orthopaedics, 44, 1875–1879.Search in Google Scholar
Meneghini, R. & Packer, A. L. (2010). The extent of multidisciplinary authorship of articles on scientometrics and bibliometrics in brazil. Interciencia, 35(7), 510–514.MeneghiniR.PackerA. L. (2010). The extent of multidisciplinary authorship of articles on scientometrics and bibliometrics in brazil. Interciencia, 35(7), 510–514.Search in Google Scholar
Minasny, B., Hartemink, A. E., McBratney, A., & Jang, H.-J. (2013). Citations and the h index of soil researchers and journals in the web of science, scopus, and google scholar. PeerJ, 1:e183.MinasnyB.HarteminkA. E.McBratneyA.JangH.-J. (2013). Citations and the h index of soil researchers and journals in the web of science, scopus, and google scholar. PeerJ, 1:e183.Search in Google Scholar
Mryglod, O., Kenna, R., Holovatch, Y., & Berche, B. (2013a). Absolute and specific measures of research group excellence. Scientometrics, 95, 115–127.MryglodO.KennaR.HolovatchY.BercheB. (2013a). Absolute and specific measures of research group excellence. Scientometrics, 95, 115–127.Search in Google Scholar
Mryglod, O., Kenna, R., Holovatch, Y., & Berche, B. (2013b). Comparison of a citation-based indicator and peer review for absolute and specific measures of research-group excellence. Scientometrics, 97, 767–777.MryglodO.KennaR.HolovatchY.BercheB. (2013b). Comparison of a citation-based indicator and peer review for absolute and specific measures of research-group excellence. Scientometrics, 97, 767–777.Search in Google Scholar
Ostertagova, E., Ostertag, O., & Kováč, J. (2014). Methodology and application of the Kruskal-Wallis test. Applied mechanics and materials, 611, 115-120.OstertagovaE.OstertagO.KováčJ. (2014). Methodology and application of the Kruskal-Wallis test. Applied mechanics and materials, 611, 115-120.Search in Google Scholar
Robinson, D. B. T., Hopkins, L., Brown, C., Abdelrahman, T., Powell, A. G., Egan, R. J., & Lewis, W. G. (2019a). Relative value of adapted novel bibliometrics in evaluating surgical academic impact and reach. World Journal of Surgery, 43, 967–972.RobinsonD. B. T.HopkinsL.BrownC.AbdelrahmanT.PowellA. G.EganR. J.LewisW. G. (2019a). Relative value of adapted novel bibliometrics in evaluating surgical academic impact and reach. World Journal of Surgery, 43, 967–972.Search in Google Scholar
Robinson, D. B. T., Hopkins, L., Brown, C., Abdelrahman, T., Powell, A. G., Egan, R. J., & Lewis, W. G. (2019b). Relative value of adapted novel bibliometrics in evaluating surgical academic impact and reach. World Journal of Surgery, 43, 967–972.RobinsonD. B. T.HopkinsL.BrownC.AbdelrahmanT.PowellA. G.EganR. J.LewisW. G. (2019b). Relative value of adapted novel bibliometrics in evaluating surgical academic impact and reach. World Journal of Surgery, 43, 967–972.Search in Google Scholar
Rodríguez‐Navarro, A. (2011). Measuring research excellence: Number of nobel prize achievements versus conventional bibliometric indicators. Journal of Documentation, 67(4), 582–600.Rodríguez‐NavarroA. (2011). Measuring research excellence: Number of nobel prize achievements versus conventional bibliometric indicators. Journal of Documentation, 67(4), 582–600.Search in Google Scholar
Rosenfeld, A. (2023). Is DBLP a good computer science journals database? Computer, 56(3), 101–108.RosenfeldA. (2023). Is DBLP a good computer science journals database? Computer, 56(3), 101–108.Search in Google Scholar
Rotem, N., Yair, G., & Shustak, E. (2021a). Dropping out of master’s degrees: Objective predictors and subjective reasons. Higher Education Research & Development, 40(5), 1070–1084.RotemN.YairG.ShustakE. (2021a). Dropping out of master’s degrees: Objective predictors and subjective reasons. Higher Education Research & Development, 40(5), 1070–1084.Search in Google Scholar
Rotem, N., Yair, G., & Shustak, E. (2021b). Open the gates wider: affirmative action and dropping out. Higher Education, 81(3), 551–566.RotemN.YairG.ShustakE. (2021b). Open the gates wider: affirmative action and dropping out. Higher Education, 81(3), 551–566.Search in Google Scholar
Sahudin, Z., Mustaffa, A. H., Abdullah, H., Pramono, S. E., Wijaya, A., & Melati, I. S. (2023). Determinants of academic research productivity in malaysia: An integration of theory of planned behaviour and social capital theory. Asian Journal of University Education, 19(3), 486–505.SahudinZ.MustaffaA. H.AbdullahH.PramonoS. E.WijayaA.MelatiI. S. (2023). Determinants of academic research productivity in malaysia: An integration of theory of planned behaviour and social capital theory. Asian Journal of University Education, 19(3), 486–505.Search in Google Scholar
Salmi, J. (2011). The road to academic excellence: Lessons of experience. The road to academic excellence: The making of world-class research universities, 323–347.SalmiJ. (2011). The road to academic excellence: Lessons of experience. The road to academic excellence: The making of world-class research universities, 323–347.Search in Google Scholar
Sedgwick, P. (2012). Pearson’s correlation coefficient. Bmj, 345.SedgwickP. (2012). Pearson’s correlation coefficient. Bmj, 345.Search in Google Scholar
Serenko, A., Marrone, M., & Dumay, J. (2022). Scientometric portraits of recognized scientists: A structured literature review. Scientometrics, 127(8), 4827–4846.SerenkoA.MarroneM.DumayJ. (2022). Scientometric portraits of recognized scientists: A structured literature review. Scientometrics, 127(8), 4827–4846.Search in Google Scholar
Shapiro, S. S. & Wilk, M. B. (1965). An analysis of variance test for normality (complete samples). Biometrika, 52(3-4), 591–611.ShapiroS. S.WilkM. B. (1965). An analysis of variance test for normality (complete samples). Biometrika, 52(3-4), 591–611.Search in Google Scholar
Singh, P., Piryani, R., Singh, V. K., & Pinto, D. (2020). Revisiting subject classification in academic databases: A comparison of the classification accuracy of web of science, scopus & dimensions. Journal of Intelligent & Fuzzy Systems, 39(2), 2471–2476.SinghP.PiryaniR.SinghV. K.PintoD. (2020). Revisiting subject classification in academic databases: A comparison of the classification accuracy of web of science, scopus & dimensions. Journal of Intelligent & Fuzzy Systems, 39(2), 2471–2476.Search in Google Scholar
Sziklai, B. R. (2021). Ranking institutions within a discipline: The steep mountain of academic excellence. Journal of Informetrics, 15(2),101133.SziklaiB. R. (2021). Ranking institutions within a discipline: The steep mountain of academic excellence. Journal of Informetrics, 15(2),101133.Search in Google Scholar
Taheri, S. & Aliakbary, S. (2022). Research trend prediction in computer science publications: a deep neural network approach. Scientometrics, 127(2), 849–869.TaheriS.AliakbaryS. (2022). Research trend prediction in computer science publications: a deep neural network approach. Scientometrics, 127(2), 849–869.Search in Google Scholar
Taylor, D. R., Venable, G. T., Jones, G. M., Lepard, J. R., Roberts, M. L., Saleh, N., … & Klimo, P. (2015). Five-year institutional bibliometric profiles for 103 US neurosurgical residency programs. Journal of neurosurgery, 123(3), 547–560.TaylorD. R.VenableG. T.JonesG. M.LepardJ. R.RobertsM. L.SalehN.KlimoP. (2015). Five-year institutional bibliometric profiles for 103 US neurosurgical residency programs. Journal of neurosurgery, 123(3), 547–560.Search in Google Scholar
Tijssen, R., Visser, M., & van Leeuwen, T. (2002). Benchmarking international scientific excellence: Are highly cited research papers an appropriate frame of reference? Scientometrics, 54(3), 381–397.TijssenR.VisserM.van LeeuwenT. (2002). Benchmarking international scientific excellence: Are highly cited research papers an appropriate frame of reference? Scientometrics, 54(3), 381–397.Search in Google Scholar
Transtrum, M. K., & Sethna, J. P. (2012). Improvements to the Levenberg-Marquardt algorithm for nonlinear leastsquares minimization. arXiv preprint arXiv:1201.5885.TranstrumM. K.SethnaJ. P. (2012). Improvements to the Levenberg-Marquardt algorithm for nonlinear leastsquares minimization. arXiv preprint arXiv:1201.5885.Search in Google Scholar
Van den Besselaar, P. & Sandström, U. (2019). Measuring researcher independence using bibliometric data: A proposal for a new performance indicator. PloS one, 14(3): e0202712.Van den BesselaarP.SandströmU. (2019). Measuring researcher independence using bibliometric data: A proposal for a new performance indicator. PloS one, 14(3): e0202712.Search in Google Scholar
Vinkler, P. (2010). The evaluation of research by scientometric indicators. Elsevier.VinklerP. (2010). The evaluation of research by scientometric indicators. Elsevier.Search in Google Scholar
Wang, J. (2013). Citation time window choice for research impact evaluation. Scientometrics, 94(3), 851–872.WangJ. (2013). Citation time window choice for research impact evaluation. Scientometrics, 94(3), 851–872.Search in Google Scholar
Wildgaard, L., Schneider, J. W., & Larsen, B. (2014). A review of the characteristics of 108 author-level bibliometric indicators. Scientometrics, 101, 125–158.WildgaardL.SchneiderJ. W.LarsenB. (2014). A review of the characteristics of 108 author-level bibliometric indicators. Scientometrics, 101, 125–158.Search in Google Scholar