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Altmetrics, or alternative metrics, refer to the newer kind of events around scholarly articles, such as the number of times the article is read, tweeted, mentioned in blog posts etc. These metrics have gained a lot of popularity during last few years and are now being collected and used in several ways, ranging from early measure of article impact to a potential indicator of societal relevance of research. However, there are several studies which have cautioned about use of altmetrics on account of quality and reliability of altmetric data, as they may be more prone to manipulations and artificial inflations. This study proposes a framework based on application of Benford's Law to evaluate the quality of altmetric data. A large sized altmetric data sample is considered and the fits with Benford's Law are computed. The analysis is performed by doing plots of the empirical data distributions and the theoretical Benford's, and by employing relevant statistical measures and tests. Results for fit on first and second leading digit of altmetric data show conformity to Benford's distribution. To further explore the usefulness of the framework, the altmetric data is subjected to artificial manipulations through a systematic process and the fits to Benford's law are reassessed to see if there are distortions. The results and analysis suggest that Benford's Law based framework can be used to test the quality of altmetric data. Relevant implications of the research are discussed. [ABSTRACT FROM AUTHOR]

The massive growth in scholarly outputs during the last few decades has resulted into the creation of several scholarly databases to index the outputs. These scholarly databases index publication records and provide different metadata fields for different kinds of usage ranging from retrieval and research evaluation to various scientometric analysis. The 'author keywords' is one such important metadata field provided by many databases and used for different text-based and thematic structure analysis. The Dimensions database, however, does not provide 'author keywords' metadata field, instead it provides automatically generated terms from the article full texts, called 'concepts'. Therefore, it is not clear whether different text-based analysis can be done with data provided by Dimensions database. Therefore, this article explores the distributional characteristics of Dimensions concepts. The Dimensions concept data obtained for a sufficiently large sample of scholarly articles is analysed through rank frequency distribution plots in the log–log space. Existence of Zipfian distribution is explored. The results indicate that Dimensions concepts adhere to the Zipfian properties which in turn indicates that Dimensions concepts have similar distributional characteristics as author keywords and hence they may have the same expressive power as that of author or index keywords for scientometric exercises. The study is novel as it is the first study to explore the distributional characteristics of the Dimensions concepts, particularly with respect to Zipfian properties, which provide the statistical foundation for understanding the Dimensions concepts and help to model and analyse them. [ABSTRACT FROM AUTHOR]

Scientific collaboration at international level has increased manifolds during last two decades. Collaboration is not only associated with higher research productivity but has also been found to be positively correlated with impact. Considering the benefits and advantages of international collaboration for the national science and technology systems of a country, policymakers in different countries have designed programs to promote international collaboration in science. This paper attempts to measure and characterize the international collaboration patterns in Indian scientific research for the last 20 years (2001–2020) using data from WoS. The existing methods from scientometrics and a new formalism of boost in productivity, citations and visibility, is used for the purpose. Analytical results show that India's international collaboration has grown with a CAGR of 12.27% during this period, rising from 20.73% internationally collaborated papers in 2001 to 32.35% internationally collaborated papers in 2020. USA, Germany, England, and China remain the top collaborating partners in terms of volume of papers, however, the relative intensity of collaboration with South Korea and Saudi Arabia has increased significantly. Among the internationally collaborated papers of India, about 50% papers have an Indian researcher as lead (first) author, and further the internationally collaborated papers of India have more than 50% authors from India. The Indian indigenous scholarly ecosystem is found to be significantly productive, but slight and heavy dependence for impact and visibility, respectively, is found on international collaborations. The probable factors shaping the Indian international collaboration and the major policy implications for India are discussed. [ABSTRACT FROM AUTHOR]

Scientific collaboration at regional and international levels has increased manifolds during the last 2 decades. The South Asian region, comprising of Afghanistan, Bangladesh, Bhutan, India, Maldives, Pakistan and Sri Lanka, habitats a significant part of the world population, and is emerging as a major knowledge producer. These South Asian countries are not only connected through shared history, language and culture, but also through an intergovernmental organization called South Asian Association for Regional Cooperation (SAARC). This article attempts to measure and characterize the research collaboration in the SAARC countries during 2001–2019. The research publication data for analysis is obtained from the Web of Science database. Different kinds of collaboration- inter, mixed, intra and domestic- among the SAARC countries are measured and analyzed through a computational analysis. Results indicate that SAARC countries collaborate more with countries outside the region than within the region. The within region collaboration has grown in volume but is still less than 1% of the total research output from the region. The collaboration is also found to vary across subject areas, with Social Science & Mathematics having higher proportion of international collaboration, Medical Science & Physics having higher mixed-collaboration, and Social Science & Environment Science having higher intra collaboration. Major implications of the results are discussed. [ABSTRACT FROM AUTHOR]