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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.

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.

This study aims to assess the validity of citation metrics based on the disciplinary representative survey.

The present project compared citation rankings for individual scientists with expert judgments collected through a survey of 818 Russian sociologists. The Russian Index of Science Citation was used to construct the general population of 3,689 Russian sociologists, to whom the survey was sent by email. The regression analyses of bibliometric indicators and peer review scores for 723 names of scholars mentioned in the survey have been undertaken.

Findings suggest that scientometric indicators predict with significant accuracy the names of the most influential sociologists and those scholars who are not mentioned while they are less relevant for prediction names which received moderate attention in the survey.

This study contributes to the research on the validity of citation metrics by focusing on scientometric indicators, not limited to traditional metrics but including non-standard publication metrics and indicators of potential metric abuse. Besides, the study presents the national bibliometric data source that is especially important for non-Western higher education systems, less presented in the Web of Science or Scopus.

The two most used citation impact indicators in the assessment of scientific journals are, nowadays, the impact factor and the h-index. However, both indicators are not field normalized (vary heavily depending on the scientific category). Furthermore, the impact factor is not robust to the presence of articles with a large number of citations, while the h-index depends on the journal size. These limitations are very important when comparing journals of different sizes and categories. The purpose of this paper is to propose an alternative citation impact indicator, based on the percentage of highly cited articles in the journal.

This alternative indicator is empirically compared with the impact factor and the h-index, considering different time windows and citation percentiles (levels of citation for considering an article as highly cited compared to others in the same year and category). The authors use four journal categories (Clarivate Analytics Web of Science) which are quite different according to the publication profiles and citation levels (Information Science & Library Science, Operations Research & Management Science, Ophthalmology, and Physics Condensed Matter).

After analyzing 20 different indicators, depending on the citation percentile and the time window in which citations are counted, the indicator that seems to best homogenize the categories is the one that considers a time window of two years and a citation level of 10 percent.

The percentage of highly cited articles in a journal is field normalized (comparable between scientific categories), independent of the journal size and also robust to the presence of articles with a high number of citations.

With the development of Web2.0 and publishing digitalization, traditional libraries and evaluation citation system can no longer indicate academic paper influence validly. Therefore, it is necessary to construct smart library and find the evaluation effect of Internet metrics-Usage.

This study puts forward four indexes of scholars’ evaluation based on Usage (total Usage (U), average Usage rate (U/N), h_u-index and p_u-index), which refer to citation indexes, takes the 35 high-output scholars in the field of library and information science in the WoS database as examples, analyzes performance of different scholars evaluation indexes based on Usage and compares the differences and correlations between “citation indicators” and “usage indicators.”

This study results show that p_u-index is the strongest index to evaluate scholars. Second, there is a high correlation and strong mechanism based on time dependence and interactions between Usage and citation. Third, compared to “citation indicators”, the “usage indicators” has a larger numerical value and wider measurement range, which can break the time limitation of citation, and scientifically evaluate young scholars and newly published paper by scholars.

This paper proposes the p_u-index – a relatively superior mathematical model for Usage and provides reference for the scholars’ evaluation policy of the smart library. This model can not only provide fair evaluation conditions for young scientists but also shorten the evaluation effect of the time lag of cited indicators. In addition, the “usage indicators” in this paper are new scientific evaluation indicators generated in the network environment. Applying it to the academic evaluation system will make the research papers widely accepted by the public and will also encourage scientists to follow the development of the Internet age and pursue research with equal emphasis on quantity and quality.

This paper aims to analyze the relationships between discourse leading indicators and citations from perspectives of integrating altmetrics indicators and tries to provide references for comprehending the quantitative indicators of scientific communication in the era of open science, constructing the evaluation indicator system of the discourse leading for academic journals and then improving the discourse leading of academic journals.

Based on the theory of communication and the new pattern of scientific communication, this paper explores the formation process of academic journals' discourse leading. This paper obtains 874,119 citations and 6,378,843 altmetrics indicators data from 65 international multidisciplinary academic journals. The relationships between indicators of discourse leading (altmetrics) and citations are studied by using descriptive statistical analysis, correlation analysis, principal component analysis, negative binomial regression analysis and marginal effects analysis. Meanwhile, the connotation and essential characteristics of the indicators, the strength and influence of the relationships are further analyzed and explored. It is proposed that academic journals' discourse leading is composed of news discourse leading, social media discourse leading, peer review discourse leading, encyclopedic discourse leading, video discourse leading and policy discourse leading.

It is discovered that the 15 altmetrics indicators data have a low degree of centralization to the center and a high degree of polarization dispersion overall; their distribution patterns do not follow the normal distributions, and their distributions have the characteristics of long-tailed right-peaked curves. Overall, 15 indicators show positive correlations and wide gaps exist in the number of mentions and coverage. The academic journals' discourse leading significantly affects total cites. When altmetrics indicators of international mainstream academic and social media platforms are used to explore the connotation and characteristics of academic journals' discourse leading, the influence or contribution of social media discourse, news discourse, video discourse, policy discourse, peer review discourse and encyclopedia discourse on the citations decreases in turn.

This study is innovative from the academic journal level to analyze the deep relationships between altmetrics indicators and citations from the perspective of correlation. First, this paper explores the formation process of academic journals' discourse leading. Second, this paper integrates altmetrics indicators to study the correlation between discourse leading indicators and citations. This study will help to enrich and improve basic theoretical issues and indicators’ composition, provide theoretical support for the construction of the discourse leading evaluation system for academic journals and provide ideas for the evaluation practice activities.

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 investigate the potential of altmetric and webometric indicators to aid with funding agencies’ evaluations of their funding schemes.

This paper analyses a range of altmetric and webometric indicators in terms of suitability for funding scheme evaluations, compares them to traditional indicators and reports some statistics derived from a pilot study with Wellcome Trust-associated publications.

Some alternative indicators have advantages to usefully complement scientometric data by reflecting a different type of impact or through being available before citation data.

The empirical part of the results is based on a single case study and does not give statistical evidence for the added value of any of the indicators.

A few selected alternative indicators can be used by funding agencies as part of their funding scheme evaluations if they are processed in ways that enable comparisons between data sets. Their evidence value is only weak, however.

This is the first analysis of altmetrics or webometrics from a funding scheme evaluation perspective.

The purpose of this paper is to introduce altmetric indicators and combine with traditional citation indicators to comprehensively evaluate the impact of academic journals from the perspective of multidimensional and multi-indicator fusion.

The authors take international multidisciplinary journals as an example, combining 14 traditional citation indicators of academic journals and introducing 14 altmetric indicators to build a comprehensive evaluation model of the impact of academic journals (academic impact and societal impact). At the same time, the authors systematically construct a journal evaluation indicator system from three dimensions. Then, the indicators data of three dimensions are evaluated by normalized processing, correlation analysis, reliability and validity analysis, PCA and factor analysis.

Two-dimensional and three-dimensional analyses can exactly provide some useful information for academic journals’ location in the respective coordinate systems. There are strong positive correlations among the measured indicators in the three dimensions, and each indicator has a significant consistency between whole and internal. The correlation coefficient between FD1 and FD2 is 0.888 with a strong positive correlation. It shows that the traditional citation indicators provided by WoS and Scopus database are highly consistent, and they are comparable and alternative in evaluating the academic impact of journals. The correlation coefficients of FD1, FD2 with FD3 are 0.831 and 0.798. There are strong positive correlations among them, which indicate that the evaluation of journals’ societal impact based on altmetrics indicator can be considered as a potential supplement to academic impact evaluation based on citation and to reflect the multidimensional nature of journals impact in an immediate way.

Multidimensional and multi-indicator perspective evaluation can provide references for the selection of impact evaluation indicators and model optimization of academic journals, and also provide new ideas for improving the status of the impact evaluation of academic journals.

The purpose of the paper is to advance a framework that can assess and analyze the value of patent portfolios. On this purpose, the framework develops a conceptual and comprehensive index, the patent portfolio value index (PPVI), to assess the patent innovation level and suggest economic-strategic guidelines.

The authors have designed and applied a framework that synthesizes into a single index the results of a multiple criteria approach, based on information derived from quantitative objective data (claims, citations, and market coverage), information related to qualitative determinants (strategic positioning and economic importance), and information derived from decision makers’ perceptions and judgments.

The authors have applied the PPVI to the 3,532 patent portfolio documents in an Italian worldwide player in aerospace and defense market. The combined analysis, provided by the PPVI and a qualitative synoptic representation, has made it possible to understand the strategic positioning and alignment of patents with the core business of the company. The results of the analysis have provided managers with the necessary suggestions regarding action items to be performed: to reinforce, license, try to dismiss, or sell some of the examined patents of the portfolios.

The PPVI supplies a quick procedure to ascertain the profitability of patents and accounts for the value of a patent portfolio from an internal business perspective.

As it is built and defined, the PPVI shows elements of novelty compared to the other indexes existing in the literature, in that it follows a multiple criteria approach by merging quantitative and qualitative information.