Scientometric Analysis of Research Activity and Collaboration Patterns in Marine Pollution Literature

K. Sudhakar, S. Thanuskodi

Abstract


The current study aims to analyze the scholarly publications of researchers in marine pollution for 30 years (from 1989 to 2018). This study intends to identify the list of core journal publications, growth rate, the productivity of authors and institutions, proportion of Indian contribution, and various similar aspects at national and international levels in the field of marine pollution. The retrieved data were analyzed using the Microsoft-Excel package as per the objectives of the study, and the data has been presented as tables and graphs. The study was designed to assess and know the growth rate of the research literature output, author productivity, quantitative and qualitative indices, collaborative trends, citation patterns, key journal’s list, and geographical distribution of publications at national and international levels in Marine pollution. The study shows an inconsistency in the Annual Growth Rate (AGR) of Marine pollution publications ranging from -35.63 to 23.69 between 1989 and 2018.  The study also shows that the maximum Degree of Collaboration (DC) was identified in the years 2014 and 2018 (0.94) and the minimum DC identified in the year 1992 (0.60). The average of DC arrived as C=0.85, i.e., 85% of collaborative authors contributed. Collaboration Index (CI) of Marine pollution literature for the study period made clear that the number of authors per publication had increased from 3.32 (1989) to 5.40 (2018). The study results indicate that the overall growth rate calculated by various scientometric methods in marine pollution has been significantly growing in recent years at the international level. On the other hand, the growth rate of Marine pollution is moderate in India.

https://dorl.net/dor/ 20.1001.1.20088302.2022.20.1.20.3


Keywords


Scientometrics; Marin Pollution; Citation Analysis; Degree of Collaboration;Doubling Time; Relative Growth Rate and Time Series Analysis

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E-ISSN: 2008-8310

   ISSN: 2008-8302