Browsing by Author "Mousumi Karmakar"

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A large-scale comparison of coverage and mentions captured by the two altmetric aggregators: Altmetric.com and PlumX
(Springer Science and Business Media B.V., 2021) Mousumi Karmakar; Sumit Kumar Banshal; Vivek Kumar Singh
The increased social media attention to scholarly articles has resulted in creation of platforms & services to track the social media transactions around them. Altmetric.com and PlumX are two such popular altmetric aggregators. Scholarly articles get mentions in different social platforms (such as Twitter, Blog, Facebook) and academic social networks (such as Mendeley, Academia and ResearchGate). The aggregators track activity and events in social media and academic social networks and provide the coverage and transaction data to researchers for various purposes. Some previous studies have compared different altmetric aggregators and found differences in the coverage and mentions captured by them. This paper attempts to revisit the question by doing a large-scale analysis of altmetric mentions captured by the two aggregators, for a set 1,785,149 publication records from Web of Science. Results obtained show that PlumX tracks more altmetric sources and captures altmetric events for a larger number of articles as compared to Altmetric.com. However, the coverage and average mentions of the two aggregators, for the same set of articles, vary across different platforms, with Altmetric.com recording higher mentions in Twitter and Blog, and PlumX recording higher mentions in Facebook and Mendeley. The article also analysed coverage and average mentions captured by the two aggregators across different document types, subjects and publishers. © 2021, Akadémiai Kiadó, Budapest, Hungary.
Does presence of social media plugins in a journal website result in higher social media attention of its research publications?
(Springer Netherlands, 2020) Mousumi Karmakar; Sumit Kumar Banshal; Vivek Kumar Singh
Social media platforms have now emerged as an important medium for wider dissemination of research articles; with authors, readers and publishers creating different kinds of social media activity about the article. Some research studies have even shown that articles that get more social media attention may get higher visibility and citations. These factors are now persuading journal publishers to integrate social media plugins in their webpages to facilitate sharing and dissemination of articles in social media platforms. Many past studies have analyzed several factors (like journal impact factor, open access, collaboration etc.) that may impact social media attention of scholarly articles. However, there are no studies to analyze whether the presence of social media plugin in a journal could result in higher social media attention of articles published in the journal. This paper aims to bridge this gap in knowledge by analyzing a sufficiently large-sized sample of 99,749 articles from 100 different journals. Results obtained show that journals that have social media plugins integrated in their webpages get significantly higher social media mentions and shares for their articles as compared to journals that do not provide such plugins. Authors and readers visiting journal webpages appear to be a major contributor to social media activity around articles published in such journals. The results suggest that publishing houses should actively provide social media plugin integration in their journal webpages to increase social media visibility (altmetric impact) of their articles. © 2020, Akadémiai Kiadó, Budapest, Hungary.
Does university–industry–government collaboration in research gets higher citation and altmetric impact? A case study from India
(Akademiai Kiado ZRt., 2022) Jyoti Paswan; Vivek Kumar Singh; Mousumi Karmakar; Prashasti Singh
Collaboration in scientific research is believed to produce more useful and impactful research. The collaboration may involve multiple researchers from one institution or researchers from different institutions. Many times, such collaborations involve institutions belonging to different categories (say University, Industry or Government). This paper attempts to analyse the University–Industry–Government collaboration in research to find out whether such collaborated research outputs attract higher bibliometric and altmetric impact. Research output data of Indian institutions for the period 2010–2018 obtained from Web of Science database is used to demonstrate the analysis. The institutions are programmatically and manually tagged into one of the three categories (University, Industry or Government) depending on their type, and the research output involving different kinds of collaboration are identified and analysed. The results indicate that research papers involving University–Industry–Government collaboration do not differ significantly in terms of citations as compared to non-collaborated papers. However, an advantage in terms of social media mentions is found for different types of University-Industry-Government collaborated papers. Collaboration between U and I category entities, G and I category entities and the UIG collaboration is seen to get advantage in terms of mentions as compared to papers that do not involve such collaboration. Probable reasons for the observed patterns and implications of the results are discussed towards the end of the paper. © 2022, Akadémiai Kiadó, Budapest, Hungary.
Indian Science Reports: a web-based scientometric portal for mapping Indian research competencies at overall and institutional levels
(Springer Science and Business Media B.V., 2022) Vivek Kumar Singh; Abhirup Nandy; Prashasti Singh; Mousumi Karmakar; Aakash Singh; Hiran H. Lathabai; Satya Swarup Srichandan; Anurag Kanaujia
The article presents an introduction to a newly created scientometric portal called Indian Science Reports, available at www.indianscience.net. The portal is designed to fulfil the need for a single integrated resource for analytical data about research competencies of India at an overall level as well as Indian institutions at an individual level. India’s research performance in terms of research output, citations, highly cited papers, international collaboration, open access levels, gender distribution and social media visibility etc. are computationally analysed using publication metadata collected from Dimensions database. The portal also provides a mechanism to look for research performance of all major Indian higher education institutions, on various standard parameters, through an institutional search. Further, a concept-based search is integrated to identify top performing Indian institutions on a given research topic. The portal, thus, provides an invaluable resource of Indian scientific research data and information, which can be used for various purposes ranging from scientometric evaluation to thrust area-based funding decisions. © 2022, Akadémiai Kiadó, Budapest, Hungary.
Measuring altmetric events: The need for Longer Observation Period and Article Level Computations
(International Society for Scientometrics and Informetrics, 2021) Mousumi Karmakar; Sumit Kumar Banshal; Vivek Kumar Singh
[No abstract available]
Measuring altmetric events: the need for longer observation period and article level computations
(Emerald Publishing, 2025) Mousumi Karmakar; Vivek Kumar Singh; Sumit Kumar Banshal
Purpose: This paper aims to explore the impact of the data observation period on the computation of altmetric measures like velocity index (VI) and half-life. Furthermore, it also attempts to determine whether article-level computations are better than computations on the whole of the data for computing such measures. Design/methodology/approach: The complete publication records for the year 2016 indexed in Web of Science and their altmetric data (original tweets) obtained from PlumX are obtained and analysed. The creation date of articles is taken from Crossref. Two time-dependent variables, namely, half-life and VI are computed. The altmetric measures are computed for all articles at different observation points, and by using whole group as well as article-level averaging. Findings: The results show that use of longer observation period significantly changes the values of different altmetric measures computed. Furthermore, use of article-level delineation is advocated for computing different measures for a more accurate representation of the true values for the article distribution. Research limitations/implications: The analytical results show that using different observation periods change the measured values of the time-related altmetric measures. It is suggested that longer observation period should be used for appropriate measurement of altmetric measures. Furthermore, the use of article-level delineation for computing the measures is advocated as a more accurate method to capture the true values of such measures. Practical implications: The research work suggests that altmetric mentions accrue for a longer period than the commonly believed short life span and therefore the altmetric measurements should not be limited to observation of early accrued data only. Social implications: The present study indicates that use of altmetric measures for research evaluation or other purposes should be based on data for a longer observation period and article-level delineation may be preferred. It contradicts the common belief that tweet accumulation about scholarly articles decay quickly. Originality/value: Several studies have shown that altmetric data correlate well with citations and hence early altmetric counts can be used to predict future citations. Inspired by these findings, majority of such monitoring and measuring exercises have focused mainly on capturing immediate altmetric event data for articles just after the publication of the paper. This paper demonstrates the impact of the observation period and article-level aggregation on such computations and suggests to use a longer observation period and article-level delineation. To the best of the authors’ knowledge, this is the first such study of its kind and presents novel findings. © 2023, Emerald Publishing Limited.
Measuring interdisciplinarity of research articles: An analysis of inter-relatedness of different parameters
(IOS Press BV, 2020) Mousumi Karmakar; Vivek Kumar Singh; David Pinto
With evolution of knowledge disciplines and cross fertilization of ideas, research outputs reported as scientific papers are now becoming more and more interdisciplinary. An interdisciplinary research work usually involves ideas and approaches from multiple disciplines of knowledge applied to solve a specific problem. In many cases the interdisciplinary areas eventually emerge as full-fledged disciplines. In the last two decades, several approaches have been proposed to measure the Interdisciplinarity of a scientific article, such as propositions based on authorship, references, set of keywords etc. Among all these approaches, reference-set based approach is most widely used. The diversity of knowledge in the reference set has been measured with three parameters, namely variety, balance, and disparity. Different studies tried to combine these measures in one way or other to propose an aggregate measure of interdisciplinarity, called integrated diversity. However, there is a lack of understanding on inter-relations between these parameters. This paper tries to look into inter-relatedness between the three parameters by analytical study on an important interdisciplinary research area, Internet of Things (IoT). Research articles in IoT, as obtained from Web of Science for the year 2018 have been analyzed to compute the three measures and understand their inter-relatedness. Results obtained show that variety and balance are negatively correlated, variety and disparity do not show a stable relatedness and balance and disparity are negatively correlated. Further, the integrated diversity measure is negatively correlated with variety and weakly positively correlated with balance and disparity. The results imply that the composite integrated diversity measure may not be a suitably constructed composite measure of interdisciplinarity. © 2020 - IOS Press and the authors. All rights reserved.
Social media coverage of research output from 100 most productive institutions in India
(Phcog.Net, 2019) Tanu Solanki; Mousumi Karmakar; Sumit Kumar Banshal; Vivek Kumar Singh
In the modern age of connected world and social media, research outcomes that are of direct interest & relevance to society are increasingly being shared and disseminated in news sources and social media platforms. Some studies have found that social media mentions of research papers can be an early indicator of their impact. India, which is now among the top 10 knowledge producers in the world, has more than 900 Universities that contribute to its research output. This paper tries to analyze as to what proportion of research output from the 100 most productive Indian institutions gets social media coverage. It is found that, while average social media coverage for India is around 28.5%, the coverage varies between 5% to 60% for different institutions. It is also observed that research output from institutions in some specific disciplines (such as Medical Science and Biological Science) attract more social media coverage as compared to others. The possible impact of geographical location (in a metro city) of an institution on social media coverage of its research output is analyzed as well. The findings present useful insight about social media coverage of research output of Indian institutions, which may be a proxy for societal relevance of the research work, and also indicate that suitable mechanisms need to be designed to promote dissemination of research results from Indian institutions in popular social media platforms. © The Author(s).
Social Media for Science-Science and Science-Society Connects: Assessing the Readiness in Indian Context through an Analysis of Social Media Visibility of Research Papers
(Phcog.Net, 2024) Vivek Kumar Singh; Mousumi Karmakar; Anurag Kanaujia; Sujit Bhattacharya
The technological advancements and emergence of new kinds of communication mediums, especially social media and networks, have brought an era of unprecedented connectivity, which can be leveraged for better science communication. This paper explores social media activity around Indian research papers with the objective of evaluating if the quantum of activity is sufficient enough to indicate that social media can be an effective medium of science communication in India. In the absence of any existing survey of social media usage by scientists in India, the paper uses altmetrics as a proxy measure to capture; science communication activities around two major classes, namely, science-science connect and science-society connect. Results indicate that social media activity around Indian research papers is relatively low as compared to the developed countries and also the world average. There is a higher activity in science-science connect (Mendeley) whereas science-society connect is less pronounced (other social media and news). The paper argues that there is a need to expose Indian research community to the opportunities that social media presents and that an appropriate use can be helpful for improved science-science and science-society connects. © 2024 Phcog.Net. All rights reserved.
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.