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A growing number of African countries are starting to produce science, technology and innovation (STI) indicators. The purpose of this paper is to provide some lessons learnt in the production and use of STI indicators in Malawi and South Africa. It is compares the two countries’ efforts to conduct Research and Development (R&D) surveys and examines whether and how STI indicators are used in policymaking processes.

The study approach is qualitative. The research methodology encompasses a thorough review of both policy and academic literature as well as some interviews.

The study demonstrates that South Africa has a relatively developed institutional arrangement for undertaking R&D and innovation surveys and developing related STI indicators. There is evidence that efforts are being made to use STI indicators to inform policymaking in the country. On the other hand, Malawi conducted its first R&D survey under the African Science, Technology and Innovation Indicators Initiative (ASTII) and has not established an institutional mechanism dedicated to producing STI indicators. There is no evidence that indicators are used in, or to inform, policymaking in the country.

Because of significant differences in STI policymaking histories, capacities and cultures of the two countries, it is not really useful to compare the STI production and use. Rather it is important to draw lessons from the efforts of the two countries.

The results suggest that the production of STI indicators should be embedded in policy processes. To be useful and effective, STI indicators production needs to be explicitly linked to policy formulation, evaluation and monitoring activities without necessarily undermining the independence of producing STI indicators.

Creating stand-alone programmes or agencies for R&D and innovation surveys without clear articulation with policymaking needs erodes opportunities of having evidence-based STI policy regimes.

Although in 2005 only South Africa and Tunisia had national programmes dedicated to the generation of R&D statistics, by the end of 2010 at least 19 African countries had experimented with conducting R&D surveys under the auspices of the ASTII of the New Partnership for Africa’s Development. These countries accumulated different experiences and consequently build different kinds of institutional capacities. Through the Malawi and South Africa case studies, some important lessons for STI indicators production and use and STI policymaking can be drawn for developing countries in general and African countries in particular.

Several bibliometric indicators that are extensively used to estimate research performance have not been validated against an external criterion of excellence. This paper aims to investigate whether this validation is possible using the number of Nobel Prize awards.

This study uses several analytical treatments of the data to investigate: whether Nobel Prize awards are sporadic events or they depend on the scientific activity of countries or institutions and can be used in research evaluation; and the association between the number of Nobel Prize achievements and conventional bibliometric indicators across countries and institutions.

This study finds that conventional bibliometric indicators, numbers of publications, citations, and top 1 per cent most cited publications, correlate with the number of Nobel Prize achievements in several advanced countries with similar research abilities. Contrarily, in countries and institutions with more variable research characteristics, there is no association between conventional bibliometric indicators and the number of Nobel Prize achievements, and their use as indicators of research excellence is not valid. In contrast, the number of national articles in Nature and Science correlates with the number of Nobel Prize achievements across countries and institutions.

Science administrators implementing research evaluations and research incentives based on conventional bibliometric indicators should consider that increasing the scores of these indicators does not imply an improvement in research excellence.

The study demonstrates that Nobel Prize achievements are not singular events that occur by chance. Therefore, the number of Nobel Prize achievements can be used to validate bibliometric indicators.

Given the magnitude of the literature, a researcher must be selective of research papers and publications in general. In other words, only papers that meet strict standards of academic integrity and adhere to reliable and credible sources should be referenced. The purpose of this paper is to approach this issue from the prism of scientometrics according to the following research questions: Is it necessary to judge the quality of scientific production? How do we evaluate scientific production? What are the tools to be used in evaluation?

This paper presents a comparative study of scientometric evaluation practices and tools. A systematic literature review is conducted based on articles published in the field of scientometrics between 1951 and 2022. To analyze data, the authors performed three different aspects of analysis: usage analysis based on classification and comparison between the different scientific evaluation practices, type and level analysis based on classifying different scientometric indicators according to their types and application levels and similarity analysis based on studying the correlation between different quantitative metrics to identify similarity between them.

This comparative study leads to classify different scientific evaluation practices into externalist and internalist approaches. The authors categorized the different quantitative metrics according to their types (impact, production and composite indicators), their levels of application (micro, meso and macro) and their use (internalist and externalist). Moreover, the similarity analysis has revealed a high correlation between several scientometric indicators such as author h-index, author publications, citations and journal citations.

The interest in this study lies deeply in identifying the strengths and weaknesses of research groups and guides their actions. This evaluation contributes to the advancement of scientific research and to the motivation of researchers. Moreover, this paper can be applied as a complete in-depth guide to help new researchers select appropriate measurements to evaluate scientific production. The selection of evaluation measures is made according to their types, usage and levels of application. Furthermore, our analysis shows the similarity between the different indicators which can limit the overuse of similar measures.

The purpose of this paper is to study the presence of highly cited papers of Nature in social media websites and tools. It also tries to examine the correlation between altmetric and bibliometric indicators.

This descriptive study was carried out using altmetric indicators. The research sample consisted of 1,000 most-cited articles in Nature. In February 2019, the bibliographic information of these articles was extracted from the Scopus database. Then, the titles of all articles were manually searched on Google, and by referring to the article in the journal website and altmetric institution, the data related to social media presence and altmetric score of articles were collected. The data were analyzed using Microsoft Excel and SPSS.

According to the results of the study, from 1,000 articles, 989 of them (98.9 per cent) were mentioned at least once in different social media websites and tools. The most used altmetric source in highly cited articles was Mendeley (98.9 per cent), followed by Citeulike (79.8 per cent) and Wikipedia (69.4 per cent). Most Tweets, blog posts, Facebook posts, news stories, readers in Mendeley, Citeulike and Connotea and Wikipedia citations belonged to the article titled “Mastering the game of Go with deep neural networks and tree search”. The highest altmetric score was 3,135 which belonged to this paper. Most tweeters and articles’ readers were from the USA. The membership type of the tweeters was public membership. In terms of fields of study, most readers were PhD students in Agricultural and Biological Sciences. Finally, the results of Spearman’s Correlation revealed positive significant statistical correlation between all altmetric indicators and received citations of highly cited articles (p-value = 0.0001).

The results of this study can help researchers, editors and editorial boards of journals better understand the importance and benefits of using social media and tools to publish articles.

Altmetrics is a relatively new field, and in particular, there are not many studies related to the presence of articles in various social media until now. Accordingly, in this study, a comprehensive altmetric analysis was carried out on 1000 most-cited articles of one of the world's most reliable journals.

The study aimed to measure scientific and social impacts of Iranian researchers' “Top Papers” in clinical medicine using citation and altmetric indicators.

In this applied descriptive-analytical study, it used scientometric analysis. A total of 166 “Top Papers” of Iranian researchers in clinical medicine category of Web of Science (WoS) database including “Highly Cited Papers” and “Hot Papers” published between 2009 and 2019 were used. Overall, 29 indicators and their data were extracted from WoS, Scopus, ResearchGate (RG) and PlumX in March 2020.

The results showed that there exists a positive correlation between the number of citations in WoS, Scopus, RG, PubMed and Crossref. In addition, it was found that there existed a positive correlation between the received citations by articles and altmetric indicators. According to the results, there is a strong correlation between RG Research Interest and citation impact. The correlation analysis on the Plum Analytics categories including “Usage”, “Capture”, “Mention”, “Social Media” and “Citation” showed the correlations between five dimensions of impact were positive and significant. The results have led the authors to think more about new metrics that can response to new developments in the new information areas.

There are limitations to access altmetric.com in Iran and cannot be used easily. On the other hand, because of considering 24 indicators, authors had to investigate only a sample of 166 top papers from Iranian researchers to present the detailed results. About nature of altmetric indicators, although they reflect the nonacademic impact of articles alongside bibliographic indicators, they still cannot be a complete representative of the influence of their owners.

This study can indicate a practical application appropriate for the future study. It would be valuable to further examine how social academic platforms construct images of impact of research and how this impacts the social impact of the university as a mission. This study suggests that social media attention to academic research can be much greater than what is shown in traditional indicators such as citation.

This study examines 29 indicators from four platforms including RG, WoS, Scopus and PlumX, simultaneously and measures the relationship among them.

Indicators of economic and social phenomena can be useful descriptive and analytical inputs for public policy. The “social indicators movement” has emerged in the last decade and is devoted to the measurement of widely‐ranging dimensions of human welfare. For the most part, questions of systematic measurement for public policy are explored here. Drawing initially on some traditions of measurement in economics, the principal aim is to provide a broad theoretical frame of reference for policy indicator design. Questions of indicator development necessarily involve ideas of suitability or validity of indicators designed for a purpose. Approaches to indicator design for the purpose of enhancing collective decision‐making—including formal model building approaches—are subsumed as special cases once a more general theory is espoused in sections II and III.

Aggregated journal‐journal citations can be used for mapping the intellectual organization of the sciences in terms of specialties because the latter can be considered as interreading communities. Can the journal‐journal citations also be used as early indicators of change by comparing the files for two subsequent years? Probabilistic entropy measures enable us to analyze changes in large datasets at different levels of aggregation and in considerable detail. Compares Journal Citation Reports of the Social Science Citation Index for 1999 with similar data for 1998 and analyzes the differences using these measures. Compares the various indicators with similar developments in the Science Citation Index. Specialty formation seems a more important mechanism in the development of the social sciences than in the natural and life sciences, but the developments in the social sciences are volatile. The use of aggregate statistics based on the Science Citation Index is ill‐advised in the case of the social sciences because of structural differences in the underlying dynamics.

The purpose of this paper is to analyze the disciplinary orientation of scientific publications that were mentioned on different social media platforms, focussing on their differences and similarities with citation counts.

Social media metrics and readership counts, associated with 500,216 publications and their citation data from the Web of Science database, were collected from Altmetric.com and Mendeley. Results are presented through descriptive statistical analyses together with science maps generated with VOSviewer.

The results confirm Mendeley as the most prevalent social media source with similar characteristics to citations in their distribution across fields and their density in average values per publication. The humanities, natural sciences, and engineering disciplines have a much lower presence of social media metrics. Twitter has a stronger focus on general medicine and social sciences. Other sources (blog, Facebook, Google+, and news media mentions) are more prominent in regards to multidisciplinary journals.

This paper reinforces the relevance of Mendeley as a social media source for analytical purposes from a disciplinary perspective, being particularly relevant for the social sciences (together with Twitter). Key implications for the use of social media metrics on the evaluation of research performance (e.g. the concentration of some social media metrics, such as blogs, news items, etc., around multidisciplinary journals) are identified.

The purpose of this paper is to investigate the usage, captures, mentions, social media and citations of highly cited papers of Library and information science (LIS).

This study is quantitative research that was conducted using scientometrics and altmetrics indicators. The research sample consists of LIS classic papers. The papers contain highly cited papers of LIS that are introduced by Google Scholar. The research data have been gathered from Google Scholar, Scopus and Plum Analytics Categories. The data analysis has been done by Excel and SPSS applications.

The data indicate that among the highly cited articles of LIS, the highest score regarding the usage, captures, mentions and social media and the most abundance of citations belong to “Citation advantage of open access articles” and “Usage patterns of collaborative tagging systems.” Based on the results of Spearman statistical tests, there is a positive significant correlation between Google Scholar Citations and all studied indicators. However, only the correlation between Google Scholar Citations with capture metrics (p-value = 0.047) and citation metrics (p-value = 0.0001) was statistically significant.

Altmetrics indicators can be used as complement traditional indicators of Scientometrics to study the impact of papers. Therefore, the Altmetrics knowledge of LIS researchers and experts and practicing new studies in this field will be very important.

The purpose of this paper is to provide theoretical basis and data support for researchers to choose appropriate international partners, provide a basis for Chinese research funding agencies, such as National Natural Science Foundation of China (NSFC) to formulate international research collaboration (IRC) strategies and policies and provide recommendations for the improvement of the internationalization level of China's basic scientific research.

Based on existing research, this study took output of “Major International (Regional) Joint Research Project” (MIJRP) funded by NSFC and participated by Chinese scholars in the meantime as the analysis object, proposed hypotheses and constructed the indicators of IRC and research output (RO). In addition, the mathematical statistics was used to compare the RO of China's IRC and nonIRC, and the statistical analysis model was used to measure the influence on RO of collaboration country's research capacity, research collaboration between China and US, scope of international research collaboration and reprint author country.

The RO of China's IRC is higher than that of nonIRC; research capacity of collaboration country has no inevitable effect on the RO of China's IRC; the RO of China's IRC participated by Americans is higher than that without American scholars; expanding the scope of China's IRC to some degree can increase RO; the RO of China's IRC led by foreigners is higher than that led by Chinese. In particular, China–US IRC and foreign scholars acting as the reprint author are two major factors for the RO of China's IRC.

Most of the traditional research on IRC are based on the co-author papers, and this study tried to analyze the characteristics and regularities on IRC from a new view of international collaboration projects, which can be a supplement to the traditional international collaboration research on co-author papers.