Lotka’s Law and Authorship distribution pattern in Global Synthetic Biology Literature

An attempt is made to examine the authorship distribution in Synthetic Biology (SB) literature and to validate Lotka\u27s law of author productivity. Authors obtained data for this study from the WOS database. A total of 12012 papers with 33151 unique authors has identified , and used for further analysis. Authors calculated the exponents n and c . Researchers employed Kolmogorov-Smirnov (K-S) test of goodness-of-fit to verify the validity of Lotka\u27s Law in SB literature. The results of this study proved that Lotka\u27s Law of author productivity does fit with SB literature based on the calculated values n = -2.45 and c= 0.74

Demographic change and industry-specific innovation patterns in Germany

In Germany, a thread to growth is perceived from demographic change. Demographic change means that a population is aging with the perspective of shrinking. The key question is whether an aging and shrinking population has enough talents to sustain the innovation process that is at the basis of our prosperity. In this paper we deal with the age distributions of inventivity. Specifically, we confirm past conjectures that inventive productivity is age dependent and unequally distributed among inventors. Additionally, we advance the new hypothesis that any age-bias in innovation activity should show up as industry-specific. The reason is that creative productivity is depending on the rate of technological change that on its part is industry specific. We test this hypothesis with European patent data for Germany.innovation, patents, age-dependent productivity, demographics, sectors

Testing Lotka’s Law and Pattern of Author Productivity in the Scholarly Publications of Artificial Intelligence

Artificial intelligence has changed our day to day life in multitude ways. AI technology is rearing itself as a driving force to be reckoned with in the largest industries in the world. AI has already engulfed our educational system, our businesses and our financial establishments. The future is definite that machines with artificial intelligence will soon be captivating over trained manual work that now is mostly cared by humans. Machines can carry out human-like tasks by new inputs as artificial intelligence makes it possible for machines to learn from experience. AI data from web of science database from 2008 to 2017 have been mapped to depict the average growth rate, relative growth rate, contribution made by authors in the view of research productivity, authorship pattern and collaboration of AI literature. The Lotka’s law on authorship productivity of AI literature has been tested to confirm the applicability of the law to the present data set. A K-S test was applied to measure the degree of agreement between the distribution of the observed set of data against the inverse general power relationship and the theoretical value of α = 2. It is found that the inverse square law of Lotka follow as such

Journal Productivity in Fishery Science an informetric analysis

Knowledge is a human resource which has the ability to consolidate the valuable results of human thinking and civilization through different times. It is the totality of understanding of nature and its features for improved quality of life of human society. Because of this, knowledge has been increasing in volume, dimension and directions. The term ‘information’ and 'knowledge' are often used as if they are interchangeable. Information is ‘potential knowledge‘ which is converted into knowledge by the integration of memory of human beings. In modern times there is a confusion on knowledge usage. Therefore an understanding of the concept ‘knowledge’ is needed for formulation of strategies in information science

Applicability of Lotka’s Law in Parasitology research output of India

This paper examines the conformity of Lotka’s law to authorship distribution in the field of parasitology using Scopus during 2007-2016. Totally, 5792 articles produced by 3473 unique first authors, was compiled for analysis. Lotka’s law was tested using both generalized and modified forms by using the formula: , the values of the exponent n and the constant c were computed; and Kolmogorov-Smirnov (K-S) and Chi-square tests were applied. The results showed that the Lotka’s law fit to the author productivity distribution pattern in parasitology literature

Mapping of Data Mining Research Productivity in India: A Scientometric Analysis

This study analyses the Indian Scientists contributions of research papers related to the topic in Data Mining was undertaken from Web of Science Databases has been used to retrieve the data for 22 years (1999-2020) by the searching the keyword “Data Mining”. The study reveals that, most of the researchers preferred to publish their research results in journals; as such 88.59% of articles were published in journals. More numbers of articles were published in the year 2019. The authorship trend shows that, out of total 1096 literature published, 95.53 % of the publication published under the joint author. It is observed that author productivity is not in agreement with Lotka\u27s law, but productivity distribution data partially fits the law when the value of Chi-square to 25212.62. Further this study also identified to analyses source wise. Degree of collaboration, Areas of research concentration, word frequency, Geographical distribution of the literature and citation analysis is also note