Libraries at University of Nebraska-Lincoln


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Ahmad, S., Ullah, S., Khan, F., & Lotka, A. J. (2012). Lotka ’ s Law of Scientific Productivity : Theory and Application. PUTAJ Humanities and Social Sciences, 127–135.

Ajiferuke, I., Burell, Q., & Tague, J. (1988). Collaborative coefficient: A single measure of the degree of collaboration in research. Scientometrics, 14(5–6), 421–433.

Ali Al-Ghamdi, Mohsin Al-Harbi, Natalie A. B. Beacom, Jennifer Dedolph, Marci Diegnan, Charles lftmann, Nancy Finley, Leann Locicero, John Middlecamp, Christine O?Regan, Faymarie Pluskota, Andrew A.R itter Scott Russell, I., & Sabat, Joseph Schneider, Maria Schoeberl, Phyllis Tragash, and B. H. Wi. (1998). Authorship in JASIS: A quantitative analysis. Katharine Sharp Review, Winter(6), 190–206.

Dhoble, S. (2017). Applicability of Lotka ’ s law in Mustard research publications in India - a scientometric study. SSARSC International Journal of Library, Information Networks and Knowledge, 2(1), 1–10.

Govindaradjou, S., & John, D. (2014). Quantitative analysis of research trends in a leading ecological journal: bibliometric study during 2003-2012. South African Journal of Libraries and Information Science, 80(1).

Goyena, R., & Fallis, A. . (2019). Summary for Policymakers. In Intergovernmental Panel on Climate Change (Ed.), Climate Change 2013 - The Physical Science Basis (Vol. 53, pp. 1–30). Cambridge: Cambridge University Press.

Kumar, S., & Senthilkumar, R. (2019). Applicability of Lotka’s law in astronomy & astrophysics research of India. Library Philosophy and Practice, 2019(January).

Kumaresan, R., Ezhilrani, R., & Vinitha, K. (2014). Lotka’s Law: A study with reference to the literature by faculities of National Institutes of Technology, India. International Journal of Library and Information Science (IJLIS), 2(1), 19–34.

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

Muthukrishnan, M., & Senthilkumar, R. (2017). Author productivity of oncology research output in India: Testing lotka’s law. International Journal of Information Dissemination and Technology, 7(3), 187.

Osareh, F., & Mostafavi, E. (2011). Lotka’s Law and authorship distribution in Computer Science using Web of Science (WoS) during 1986–2009. Collnet Journal of Scientometrics and Information Management, 5(2), 171–183.

Pao, M.L. (1985). Lotka's law: A testing procedure. Information Processing & Management, 21(4), 305-320

Senthilkumar R, U. G. (2016). Scientometric analysis of Astrophysics research output in India. Kongunadu Research Journal, 3(1), 84–87.

Tsai, H.-H. (2012). Global data mining: An empirical study of current trends, future forecasts and technology diffusions. Expert Systems with Applications, 39(9), 8172–8181.

Van Praag, M. C., & Van Praag, B. M. S. (2008). The benefits of being economics professor A(rather than Z). Economica, 75(300), 782–796.

Zabed Ahmed, S., & Anisur Rahman, M. (2009). Lotka’s law and authorship distribution in nutrition research in Bangladesh. Annals of Library and Information Studies, 56(2), 95–102.


The present study investigates authorship trends and productivity among LIS professionals who contributed journal articles in the selected 12 peer reviewed LIS journals of India, US and UK. For the purpose of the study four periodicals from each country are chosen during the period 2007 to 2017. The results analyzed proved that journal wise author distribution is highest in the published literature of UK with (3546) authors followed by India with (3162) and US (2420) authors. The obtained values of ᵪ²= 66.331, ρ=0.05 found that there is an association between type of authorship and country. As India and UK accounted for more number of collaborative works while US has large number of solo article contributions. The data analyzed shows preference towards collaborative research in all the three countries with little variations. Lotka’s law have been applied and tested using Pao’s method and verified through Kolmgorov-Smirnov (KS) test. The application of Lotka’s law when applied individually on author’s data set of published literature of India with Dmax value=0.0238 and critical value=0.046, proves that observed authorship data holds good for Lotka’s law in the authors’ data . But with Dmax value=0.1362 and CV=0.04 in the author distribution of US and D max value=0.2520 and CV=0.04 of UK, does not support lotka’s law. Overall the results of the K-S tests proved that author productivity distribution does not fits Lotka’s law in the subject of library and information science in scholarly research output in Library and information science published journal literature of US and UK.