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The purpose of this paper is to provide insights on the improvement of academic impact and social attention of Chinese collaboration articles from the perspective of altmetrics.

The authors retrieved articles which are from the Chinese Academy of Sciences (CAS) and indexed by Nature Index as sampled articles. With the methods of distribution analysis, comparative analysis and correlation analysis, authors compare the coverage differences of altmetric sources for CAS Chinese articles and CAS international articles, and analyze the correlation between the collaborative information and the altmetric indicators.

Results show that the coverage of altmetric sources for CAS international articles is greater than that for CAS Chinese articles. Mendeley and Twitter cover a higher percentage of collaborative articles than other sources studied. Collaborative information, such as number of collaborating countries, number of collaborating institutions, and number of collaborating authors, show moderate or low correlation with altmetric indicator counts. Mendeley readership has a moderate correlation with altmetric indicators like tweets, news outlets and blog posts.

International scientific collaboration at different levels improves attention, academic impact and social impact of articles. International collaboration and altmetrics indicators supplement each other. The results of this study can help us better understand the relationship between altmetrics indicators of articles and collaborative information of articles. It is of great significance to evaluate the influence of Chinese articles, as well as help to improve the academic impact and social attention of Chinese collaboration articles.

To the best of authors’ knowledge, few studies focus on the use of altmetrics to assess publications produced through Chinese academic collaboration. This study is one of a few attempts that include the number of collaborating countries, number of collaborating institutions, and number of collaborating authors of scientific collaboration into the discussion of altmetric indicators and figured out the relationship among them.

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 first purpose of the present study is to investigate the coverage of journal articles in Physics in various sources of altmetrics. Secondly, the study investigates the relationship between altmetrics and citations. Finally, the study also investigates whether the relationship between citations and altmetrics was stronger or weaker for those articles that had been mentioned at least once in the sources of altmetrics.

The journal articles in Physics having at least one author from an Indian Institution and published during 2014–2018 in sources of altmetrics have been investigated. Altmetric.com was used for collecting altmetrics data. Spearman’s rank correlation coefficient (ρ) has been used as the data found to be skewed.

The highest coverage was found on Twitter (22.68%), followed by Facebook (3.62%) and blogs (2.18%). The coverage in the rest of the sources was less than 1%. The average Twitter mentions for journal articles tweeted at least once was found to be 4 (3.99) and for Facebook mentions, it was found to be 1.48. Correlations between Twitter mentions–citations and Facebook mentions–citation were found to be statistically significant but low to weak positive.

The study concludes that due to the low coverage of journal articles, altmetrics should be used cautiously for research evaluation keeping in mind the disciplinary differences. The study also suggests that altmetrics can function as complementary to citation-based metrics.

The study is one of the first large scale altmetrics studies dealing with research in Physics. Also, Indian research has not been attended to in the altmetrics literature and the present study shall fill that void.

The purpose of this paper is to analyze the capabilities, functionalities and appropriateness of Altmetric.com as a data source for the bibliometric analysis of books in comparison to PlumX.

The authors perform an exploratory analysis on the metrics the Altmetric Explorer for Institutions, platform offers for books. The authors use two distinct data sets of books. On the one hand, the authors analyze the Book Collection included in Altmetric.com. On the other hand, the authors use Clarivate’s Master Book List, to analyze Altmetric.com’s capabilities to download and merge data with external databases. Finally, the authors compare the findings with those obtained in a previous study performed in PlumX.

Altmetric.com combines and orderly tracks a set of data sources combined by DOI identifiers to retrieve metadata from books, being Google Books its main provider. It also retrieves information from commercial publishers and from some Open Access initiatives, including those led by university libraries, such as Harvard Library. We find issues with linkages between records and mentions or ISBN discrepancies. Furthermore, the authors find that automatic bots affect greatly Wikipedia mentions to books. The comparison with PlumX suggests that none of these tools provide a complete picture of the social attention generated by books and are rather complementary than comparable tools.

This study targets different audience which can benefit from the findings. First, bibliometricians and researchers who seek for alternative sources to develop bibliometric analyses of books, with a special focus on the Social Sciences and Humanities fields. Second, librarians and research managers who are the main clients to which these tools are directed. Third, Altmetric.com itself as well as other altmetric providers who might get a better understanding of the limitations users encounter and improve this promising tool.

This is the first study to analyze Altmetric.com’s functionalities and capabilities for providing metric data for books and to compare results from this platform, with those obtained via PlumX.

The purpose of this study is to contribute to the understanding of how the potential of altmetrics varies around the world by measuring the percentage of articles with non-zero metrics (coverage) for articles published from a developing region (Latin America).

This study uses article metadata from a prominent Latin American journal portal, SciELO, and combines it with altmetrics data from Altmetric.com and with data collected by author-written scripts. The study is primarily descriptive, focusing on coverage levels disaggregated by year, country, subject area, and language.

Coverage levels for most of the social media sources studied was zero or negligible. Only three metrics had coverage levels above 2 per cent – Mendeley, Twitter, and Facebook. Of these, Twitter showed the most significant differences with previous studies. Mendeley coverage levels reach those found by previous studies, but it takes up to two years longer for articles to be saved in the reference manager. For the most recent year, coverage was less than half than what was found in previous studies. The coverage levels of Facebook appear similar (around 3 per cent) to that of previous studies.

The Altmetric.com data used for some of the analyses were collected for a six month period. For other analyses, Altmetric.com data were only available for a single country (Brazil).

The results of this study have implications for the altmetrics research community and for any stakeholders interested in using altmetrics for evaluation. It suggests the need of careful sample selection when wishing to make generalizable claims about altmetrics.

Hicks et al. (2015) have formulated the so-called Leiden manifesto, in which they have assembled the ten principles for a meaningful evaluation of research on the basis of bibliometric data. The paper aims to discuss this issue.

In this work the attempt is made to indicate the relevance of the Leiden manifesto for altmetrics.

As shown by the discussion of the ten principles against the background of the knowledge about and the research into altmetrics, the principles also have a great importance for altmetrics and should be taken into account in their application.

Altmetrics is already frequently used in the area of research evaluation. Thus, it is important that the user of altmetrics data knows the relevance of the Leiden manifesto also in this area.

The purpose of this paper is to contribute to the understanding of altmetrics in different disciplines of social science: first, by investigating the current richness and future potential of altmetrics in the selected social science disciplines and then by evaluating the validity of altmetrics as indicators of research impact in each discipline through correlation analysis.

This study uses three approaches to understand the current richness and future potential of ten altmetric measures in nine selected disciplines: first, investigate the distribution and trend of altmetric data; second, verify the relationship between citation rate and altmetric presence of the discipline using Pearson correlation; and third, perform word frequency analysis on tweets to understand different altmetric presence in different disciplines. In addition, this study uses Spearman and sign test to find the correlation between altmetrics and citation counts for the articles that receive altmetric mention(s) to test the validity of altmetrics as indicators of research impact.

There is a steady increase in the number of articles that receive altmetric mentions in all disciplines studied. In general, disciplines with higher citation rates have higher altmetric presence. At the same time, altmetrics are also an effective complement to citation in disciplines with low citation rates. There is a moderate correlation with Mendeley and significant but weak correlations with Tweets and CiteULike in seven disciplines. Altmetrics appear effective as a predictor of citation counts in seven out of nine disciplines studied. However, there is low presence and lack of correlation with citation count in business-finance and law disciplines.

This paper furthers the understanding of altmetrics in social science disciplines. It reveals the disciplines where altmetrics are most effective, potentially useful, and fairly applicable. In addition, it presents evidence that altmetrics are an effective complement to citation in disciplines with low citation rates.

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.

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 purpose of this case study is to investigate the usefulness of altmetrics for measuring the broader impact of research.

This case study is based on a sample of 1,082 the Public Library of Science (PLOS) journal articles recommended in F1000. The data set includes altmetrics which were provided by PLOS. The F1000 data set contains tags on papers which were assigned by experts to characterise them.

The most relevant tag for altmetric research is “good for teaching”, as it is assigned to papers which could be of interest to a wider circle of readers than the peers in a specialised area. One could expect papers with this tag to be mentioned more often on Facebook and Twitter than those without this tag. The results from regression models were able to confirm these expectations: papers with this tag show significantly higher Facebook and Twitter counts than papers without this tag. This clear association could not be seen with Mendeley or Figshare counts (that is with counts from platforms which are chiefly of interest in a scientific context).

The results of the current study indicate that Facebook and Twitter, but not Figshare or Mendeley, might provide an indication of which papers are of interest to a broader circle of readers (and not only for the peers in a specialist area), and could therefore be useful for the measurement of the societal impact of research.