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Social interaction applications and reference tools are actively used by researchers to share and manage their research publications. Thus, this paper aims to determine the scholarly impact of selected Indian central universities.

This study analyzed 669 articles having both Dimensions citations and Altmetric attention scores published by 35 Indian central universities for 4 subfields of Computer Science using Altmetric Explorer. This paper determined each university’s contribution in the studied subfields of Computer Science and the correlation among Altmetric attention score (aggregated and individual), Dimensions citation, and Mendeley readership counts for all 669 articles and stratified percentile sets of top 25%, and top 50% of the overall number of articles.

The findings showed that Jawaharlal Nehru University had the maximum Altmetric attention score, Banaras Hindu University received the maximum Dimensions citation, and University of Hyderabad (UoH) received the maximum number of Mendeley readers. Each central university was examined individually and then ranked based on their median values of Dimensions citations and Altmetric attention scores. Further, Twitter had the maximum Altmetric coverage, followed by Google+, Patent and Facebook for the retrieved articles. A significant strong positive correlation was observed between the Dimensions citation and Mendeley readership counts for all the three categories.

Both Altmetric attention scores and Dimensions citations can help funding agencies to assess and evaluate the research productivity of these universities, thus, making important decisions such as increasing, decreasing, re-distributing their funds.

The current body of research is focused mostly on relationships between citations and individual Altmetric indicators predominantly. For most of the studies, the citations were retrieved from Scopus, Web of Science or Google Scholar database. It was observed that by far, no study had examined the relationship between citations retrieved from Dimensions database, Altmetrics scores (both aggregated and individual) and Mendeley readership counts.

Scientific impact is traditionally assessed with citation-based metrics. Recently, altmetric indices have been introduced to measure scientific impact both within academia and among the general public. However, little research has investigated the association between the linguistic features of research article titles and received online attention. To address this issue, the authors examined in the present study the relationship between a series of title features and altmetric attention scores.

The data included 8,658 titles of Science articles. The authors extracted six features from the title corpus (i.e. mean word length, lexical sophistication, lexical density, title length, syntactic dependency length and sentiment score). The authors performed Spearman’s rank analyses to analyze the correlations between these features and online impact. The authors then conducted a stepwise backward multiple regression to identify predictors for the articles' online impact.

The correlation analyses revealed weak but significant correlations between all six title features and the altmetric attention scores. The regression analysis showed that four linguistic features of titles (mean word length, lexical sophistication, title length and sentiment score) have modest predictive effects on the online impact of research articles.

In the internet era with the widespread use of social media and online platforms, it is becoming increasingly important for researchers to adapt to the changing context of research evaluation. This study identifies several linguistic features that deserve scholars’ attention in the writing of article titles. It also has practical implications for academic administrators and pedagogical implications for instructors of academic writing courses.

Since the development of web 2.0, there has been a paradigm shift in methods of knowledge sharing. This has equally impacted on techniques of research evaluation. Many scholars have argued that the social utilization of research is hardly reflected in the traditional methods of research evaluation. The purpose of this paper is to determine the research impact of Library and Information Science (LIS) journals using Web of Science (WoS), Scopus and Google Scholar (GS) and then examine whether there is a correlation between their citations and altmetric attentions.

This paper is an attempt to contribute to this discussion with focus on the field of LIS. This paper adopted descriptive informatics to analyze LIS journals. The paper extracted citation data from WoS, Scopus and GS, and altmetric attentions from 85 LIS journals indexed by WoS. Further, 18 journals with high altmetric attention were identified, while 9 of these maintained consistent presence in the three databases used.

Findings show that of these databases, citation data from GS was found to have a high correlation with altmetric attention, while the other two databases maintained moderate correlations with altmetric attention. The paper also found a positive but non-significant correlation between citation scores and altmetric attention in the nine journals that maintained consistent presence in the three databases.

The findings of this paper will be useful to librarians in selection of relevant journals for their libraries and also will assist authors in the choice of publication outlets for their papers particularly when considering journals that have visibility and research impact.

The originality of the paper lies on empirical evidences from the citation and altmetric data extracted from the databases used for the paper.

The study showcases the social impact (online attention) of funded research compared to nonfunded for the BRICS nations. The key themes achieving online attention across the funded and nonfunded publications have also been identified.

A total of 1,507,931 articles published across the BRICS nations for a period of three (03) years were downloaded from the Clarivate Analytics' InCites database of Web of Science (WoS). “Funding Acknowledgement Analysis (FAA)” was used to identify the funded and nonfunded publications. The altmetric score of the top highly cited (1%) publications was gauged from the largest altmetric data provider, “Altmetric.com”, using the DOI of each publication. One-way ANOVA test was used to know the impact of funding on the mentions (altmetrics) across different data sources covered by Altmetric.com. The highly predominant keywords (hotspots) have been mapped using bibliometric software, “VOSviewer”.

The mentions across all the altmetric sources for funded research are higher compared to nonfunded research for all nations. It indicates the altmetric advantage for funded research, as funded publications are more discussed, tweeted, shared and have more readers and citations; thus, acquiring more social impact/online attention compared to nonfunded publications. The difference in means for funded and nonfunded publications varies across various altmetric sources and nations. Further, the authors’ keyword analysis reveals the prominence of the respective nation names in publications of the BRICS.

The study showcases the utility of indexing the funding information and whether research funding increases social impact return (online attention). It presents altmetrics as an important impact assessment and evaluation framework indicator, adding one more dimension to the research performance. The linking of funding information with the altmetric score can be used to assess the online attention and multi-flavoured impact of a particular funding programme and source/agency of a nation so that necessary strategies would be framed to improve the reach and impact of funded research. It identifies countries that achieve significant online attention for their funded publications compared to nonfunded ones, along with the key themes that can be utilised to frame research and investment plans.

The study represents the social impact of funded research compared to nonfunded across the BRICS nations.

The purpose of this study is to assess the value of altmetrics or other indicators, showcasing the impact of academic output, which is seen too often correlated with the citation count.

This study considered three reputed journals of Library and Information Science (LIS) published by Elsevier. A total of 1,164 articles were found in these journals from 2016 to 2020 and the relationships between altmetric attention scores (AAS) and citations were examined. The analysis was extended to compare the grouped data set based on percentile ranks of AAS like top 50%, top 25%, top 10% and top 1%.

Using Spearman correlation analysis, the findings reveal a positive correlation between AAS and citations with different significant levels for all articles, and articles with AAS, as well as for normalized AAS in the top 50%, top 25%, top 10% and top 1% data set. For the three journals International Journal of Information Management (IJIM), Journal of Informetrics (JIF) and Library and Information Science Research (LISR), a significant positive correlation is observed across all data sets. But an unexpected result was observed: in the case of the top 50% of articles for the IJIM and JIF showed no significant correlation but the LISR journal showed a positive correlation for the whole data set. This journal though has fewer articles in comparison to the other two.

A source item that is highly cited may not be having high social media attention as reflected in the findings. This demarcates AAS with citations implying various factors on which these measurements are dependent. The study distinguishes these metrics lucidly. There is not a single guideline or uniformity in assessing the correlation found. But the problem is that the interpretation of the correlation strength affects the conclusion of the study. Moreover, this study will be a role model as a draft for librarians to select relevant journals for their libraries and will facilitate authors in the choice of the publication outlets for their papers, particularly concerning the journals that have both visibility and research impact.

The study reported devising a comprehensive tool to validate AAS as a measure of scholarly impact to include appropriate social media sources and verify its relationship with other metrics. To the best of the authors’ knowledge, this paper is the first attempt to discover the correlation between AAS and citations for the highly impactful LIS journal published by Elsevier. The empirical evidence lies in the citation and altmetric data extracted from the dimension database.

This paper aims to assess the impact of research in the field of scientometrics by using the altmetrics (social media metrics) approach.

This is an applied study which uses scientometric and altmetrics methods. The research population consists of the studies and their citations published in the two core journals (Scientometrics and Journal of Informetrics) in a period of five years (included 1,738 papers and 11,504 citations). Collecting and extracting the studies directly was carried from Springer and ScienceDirect databases. The Altmetric Explorer, a service provided by Altmetric.com, was used to collect data on studies from various sources (www.altmetric.com/). The research studies with the altmetric scores were identified (included 830 papers). The altmetric scores represent the quantity and quality of attention that the study has received on social media. The association between altmetric scores and citation indicators was investigated by using correlation tests.

The findings indicated a significant, positive and weak statistical relationship between the number of citations of the studies published in the field of scientometrics and the altmetric scores of these studies, as well as the number of readers of these studies in the two social networks (Mendeley and Citeulike) with the number of their citations. In this study, there was no statistically significant relationship between the number of citations of the studies and the number of readers on Twitter. In sum, the above findings suggest that some social networks and their indices can be representations of the impact of scientific papers, similar citations. However, owing to the weakness of the correlation coefficients, the replacement of these two categories of indicators is not recommended, but it is possible to use the altmetrics indicators as complementary scientometrics indicators in evaluating the impact of research.

Investigating the impact of research on social media can reflect the social impact of research and can also be useful for libraries, universities, and research organizations in planning, budgeting, and resource allocation processes.

Altmetrics is a complementary method in scientometrics for evaluating the performance of individuals, organizations, institutions and countries in social media. Due to the large volume of data related to the interactions in science, technology and innovation, there is no choice but to develop and implement accurate models for analysis and decision making. The Quadruple Helix Model examines the scientific outcomes in four spaces of innovation, knowledge, consensus and government with a distinctive attention to the “innovation space”. In other words, it aims to find the connection between the academic space and other sectors of a society (public, media and government) to see if scientific outputs respond appropriately to their needs.

The present paper studied the impact of health-related researches in D8 countries) including Iran, Turkey, Pakistan, Bangladesh, Indonesia, Malaysia, Egypt and Nigeria) using the Altmetrics scores of their indexed journal in the Web of Science (WOS). The results demonstrated distribution of interactions of the mentioned four spaces in health science researches in terms of social media, geographical distribution and theme for D8 countries. This was conducted using content analysis, scientometric and altmetric indicators in the WOS and Altmetrics.com databases.

In D8 countries, more interaction has taken place in the knowledge and innovation spaces; however, there exist Quadruple imbalances in these countries. Moreover, some interactions have been observed in all social networks, displaying that users consider health topics in D8 countries, and clinical sciences has gotten more interaction in all the four spaces.

The application of this model using altmetrics data with current approach has been conducted for the first time.

The rapid spread and severity of the coronavirus (COVID-19) virus have prompted a spate of scholarly research that deals with the pandemic. The purpose of this study is to measure and assess the coverage of COVID-19 research on social media and the engagement of readers with COVID-19 research on social media outlets.

An altmetric analysis was carried out in three phases. The first focused on retrieving all papers related to COVID-19. Phase two of the research aimed to measure the presence of the retrieved papers on social media using altmetric application programming interface (API). The third phase aimed to measure Mendeley readership categories using Mendeley API to extract data of readership from Mendeley for each paper.

The study suggests that while social media platforms do not give accurate measures of the impact as given by citations, they can be used to portray the social impact of the scholarly outputs and indicate the effectiveness of COVID-19 research. The results confirm a positive correlation between the number of citations to articles in databases such as Scopus and the number of views on social media sites such as Mendeley and Twitter. The results of the current study indicated that social media could serve as an indicator of the number of citations of scientific articles.

This study’s limitation is that the studied articles’ altmetrics performance was examined using only one of the altmetrics data service providers (altmetrics database). Hence, future research should explore altmetrics on the topic using more than one platform. Another limitation of the current research is that it did not explore the academic social media role in spreading fake information as the scope was limited to scholarly outputs on social media. The practical contribution of the current research is that it informs scholars about the impact of social media platforms on the spread and visibility of COVID-19 research. Also, it can help researchers better understand the importance of published COVID-19 research using social media.

This paper provides insight into the impact of COVID-19 research on social media. The paper helps to provide an understanding of how people engage with health research using altmetrics scores, which can be used as indicators of research performance.

The purpose of this study is to apply altmetrics and bibliometric indicators on the top 100 most mentioned articles published related to the sustainable development goal (SDG)-13, Climate Action.

The authors used the Altmetric Explorer’s SDGs filter to extract the most mentioned articles belonging to Climate Action and their other characteristics, such as DOI, titles, tools mentioning them and their demographic descriptions. The same set of papers was searched in the Dimensions database to extract them in the format importable in R-studio to check the distribution of papers across various journals and identify their subject category, countries and institutions publishing these papers. Further, SPSS was used to check the correlation between altmetric attention score (AAS) and citations.

The results of the paper showed the mean of AAS and the citations received by the articles was 3,556.35 and 304.04, respectively. Twitter has been the most used social media platform for mentioning the research related to climate action, covering 88.1% of the total mentions. The Twitter and the News mention demographics show the USA contributing the most tweet mentions (15.2%) as well as news mentions (57.65%) to the papers. Also, the USA has solely published 49 papers from the total papers selected for the study. The papers were published in 31 journals most of them belonging to the quartile first (Q1) category and primarily belonged to the subject category “Earth Sciences.” Pearson’s correlational method showed a significant but low positive correlation between AAS and citation counts (r = 0.365, p = <0.001) and a strong positive correlation between the citations and Mendeley readership counts (r = 0.907).

The research is original in nature and discovered very interesting results about climate action using altmetric and bibliometric techniques.

The authors explore the emergence of altmetrics and Open Access (OA) publishing and discuss why their adoption in the management field lags behind other fields such as life sciences. The authors draw on the status literature to discuss the knowledge production and consumption underpinned by the ‘Impact Factor’ metric and high-status ‘Toll Access’ journals and their implications. The authors explain the rise of altmetrics and OA publishing and their implications on the production and consumption of knowledge. The authors then examine the current situation, challenges and offer reflections on the management field’s progression towards a more open research regime in the digital era.