Browsing by Author "Philipp Mayr"

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Analysing author name mentions in citation contexts of highly cited publications
(CEUR-WS, 2019) Rajesh Piryani; Wolfgang Otto; Philipp Mayr; Vivek Kumar Singh
In this paper, we are analysing author name mentions in citation contexts of highly cited articles in a PLOS ONE corpus. First, we have identified author mentions in our corpus of citation contexts. Then, we examined frequent nouns and verbs in the neighbourhood of the identified author mentions using n-grams and utilized these top nouns and verbs to identify the most frequent patterns. We observed that most frequent patterns are associated with the methods which are proposed in the corresponding highly cited references. © 2019 CEUR-WS. All rights reserved.
Comparing research performance of private universities in India with IITs, central universities and NITs
(Indian Academy of Sciences, 2019) Sumit Kumar Banshal; Vivek Kumar Singh; Philipp Mayr
During the last two decades the number of private universities in India has increased significantly. According to AISHE report of 2016, out of 799 universities in India, 277 are private universities, i.e. one out of every three universities in India is a private university. A significant proportion of colleges (about 78%) are also privately managed, as they do not contribute much to research activities and hence are not included in this analysis. Private universities are now becoming a major component of the Indian higher education system. Some of the private universities are exclusively positioning and projecting themselves as universities for high quality research and innovation. A few of them are now well placed in the national-level NIRF ranking framework. It is in this context that this paper presents a comparative account of research performance of the 25 most productive private universities with the set of Indian Institutes of Technology (IITs), Central Universities (CUs) and National Institutes of Technology (NITs), all of which have a well-established environment and culture of research. A set-based comparison methodology is followed. The results show good performance of private universities in research, especially in terms of output and rate of growth of output. However, on quality and productivity per capita and per rupee spent, they have a long way to go to match the performance levels of well-established centrally funded higher education institutions of India. This study presents detailed scientometric assessment of some most productive private universities in India. © 2019 Current Science Association, Bengaluru.
Disciplinary variations in altmetric coverage of scholarly articles
(International Society for Scientometrics and Informetrics, 2019) Sumit Kumar Banshal; Vivek Kumar Singh; Pranab K. Muhuri; Philipp Mayr
The popular social media platforms are now making it possible for scholarly articles to be shared rapidly in different forms, which in turn can significantly improve the visibility and reach of articles. Many authors are now utilizing the social media platforms to disseminate their scholarly articles (often as pre- or post- prints) beyond the paywalls of journals. It is however not very well established if the level of social media coverage and attention of scholarly articles is same across all research disciplines or there exist discipline-wise variations. This paper aims to explore the disciplinary variations in coverage and altmetric attention by analyzing a significantly large amount of data from Web of Science and Altmetric.com. Results obtained show interesting patterns. Medical Sciences and Biology are found to account for more than 50% of all instances in Altmetrics. In terms of coverage, disciplines like Biology, Medical Science and Multidisciplinary Sciences have more than 60% of their articles covered in Altmetrics, whereas disciplines like Engineering, Mathematics and Material Science have less than 25% of their articles covered in Altmetrics. The coverage percentages further vary across different altmetric platforms, with Twitter and Mendeley having much higher overall coverage than Facebook and News. Disciplinary variations in coverage are also found in different altmetric platforms, with variations as large as 7.5% for Engineering discipline to 55.7% for Multidisciplinary in Twitter. The paper also looks into the possible role of source of publication in altmetric coverage level of articles. Interestingly, some journals are found to have a higher altmetric coverage in comparison to the average altmetric coverage level of that discipline. © 2019 17th International Conference on Scientometrics and Informetrics, ISSI 2019 - Proceedings. All rights reserved.
Highly cited references in PLOS ONE and their in-text usage over time
(International Society for Scientometrics and Informetrics, 2019) Wolfgang Otto; Behnam Ghavimi; Philipp Mayr; Rajesh Piryani; Vivek Kumar Singh
In this article, we describe highly cited publications in a PLOS ONE full-text corpus. For these publications, we analyse the citation contexts concerning their position in the text and their age at the time of citing. By selecting the perspective of highly cited papers, we can distinguish them based on the context during citation even if we do not have any other information source or metrics. We describe the top cited references based on how, when and in which context they are cited. The focus of this study is on a time perspective to explain the nature of the reception of highly cited papers. We have found that these references are distinguishable by the IMRaD sections of their citation. And further, we can show that the section usage of highly cited papers is time-dependent: the longer the citation interval, the higher the probability that a reference is cited in a method section. © 2019 17th International Conference on Scientometrics and Informetrics, ISSI 2019 - Proceedings. All rights reserved.
How much research output from India gets social media attention?
(Indian Academy of Sciences, 2019) Sumit Kumar Banshal; Vivek Kumar Singh; Pranab K. Muhuri; Philipp Mayr
Scholarly articles are now increasingly being mentioned and discussed in social media platforms, sometimes even as pre- or post-print version uploads. Measures of social media mentions and coverage are now emerging as an alternative indicator of impact of scholarly articles. This article aims to explore how much scholarly research output from India is covered in different social media platforms, and how similar or different it is from the world average. It also analyses the disciplinewise variations in coverage and altmetric attention for Indian research output, including a comparison with the world average. Results obtained show interesting patterns. Only 28.5% of the total research output from India is covered in social media platforms, which is about 18% less than the world average. ResearchGate and Mendeley are the most popular social media platforms in India for scholarly article coverage. In terms of discipline-wise variation, medical sciences and biological sciences have relatively higher coverage across different platforms compared to disciplines like information science and engineering. © 2019 Current Science Association, Bengaluru.
Patterns in the Growth and Thematic Evolution of Artificial Intelligence Research: A Study Using Bradford Distribution of Productivity and Path Analysis
(Wiley-Hindawi, 2024) Solanki Gupta; Anurag Kanaujia; Hiran H. Lathabai; Vivek Kumar Singh; Philipp Mayr
Artificial intelligence (AI) has emerged as a transformative technology with applications across multiple domains. The corpus of work related to the field of AI has grown significantly in volume as well as in terms of the application of AI in wider domains. However, given the wide application of AI in diverse areas, the measurement and characterization of the span of AI research is often a challenging task. Bibliometrics is a well-established method in the scientific community to measure the patterns and impact of research. It however has also received significant criticism for its overemphasis on the macroscopic picture and the inability to provide a deep understanding of growth and thematic structure of knowledge-creation activities. Therefore, this study presents a framework comprising of two techniques, namely, Bradford's distribution and path analysis to characterize the growth and thematic evolution of the discipline. While the Bradford distribution provides a macroscopic view of artificial intelligence research in terms of patterns of growth, the path analysis method presents a microscopic analysis of the thematic evolutionary trajectories, thereby completing the analytical framework. Detailed insights into the evolution of each subdomain are drawn, major techniques employed in various AI applications are identified, and some relevant implications are discussed to demonstrate the usefulness of the analyses. © 2024 Solanki Gupta et al.
The journal coverage of Web of Science, Scopus and Dimensions: A comparative analysis
(Springer Science and Business Media B.V., 2021) Vivek Kumar Singh; Prashasti Singh; Mousumi Karmakar; Jacqueline Leta; Philipp Mayr
Traditionally, Web of Science and Scopus have been the two most widely used databases for bibliometric analyses. However, during the last few years some new scholarly databases, such as Dimensions, have come up. Several previous studies have compared different databases, either through a direct comparison of article coverage or by comparing the citations across the databases. This article aims to present a comparative analysis of the journal coverage of the three databases (Web of Science, Scopus and Dimensions), with the objective to describe, understand and visualize the differences in them. The most recent master journal lists of the three databases is used for analysis. The results indicate that the databases have significantly different journal coverage, with the Web of Science being most selective and Dimensions being the most exhaustive. About 99.11% and 96.61% of the journals indexed in Web of Science are also indexed in Scopus and Dimensions, respectively. Scopus has 96.42% of its indexed journals also covered by Dimensions. Dimensions database has the most exhaustive journal coverage, with 82.22% more journals than Web of Science and 48.17% more journals than Scopus. This article also analysed the research outputs for 20 selected countries for the 2010–2018 period, as indexed in the three databases, and identified database-induced variations in research output volume, rank, global share and subject area composition for different countries. It is found that there are clearly visible variations in the research output from different countries in the three databases, along with differential coverage of different subject areas by the three databases. The analytical study provides an informative and practically useful picture of the journal coverage of Web of Science, Scopus and Dimensions databases. © 2021, Akadémiai Kiadó, Budapest, Hungary.