An extensive analysis of the presence of altmetric data for Web of Science publications across subject fields and research topics

Time for Medicine and Public Health to Leave Platform X

Unlabelled

For more than 50 years, digital technologies have been employed for the creation and distribution of knowledge in health services. In the last decade, digital social media have been developed for applications in clinical decision support and population health monitoring. Recently, these technologies have also been used for knowledge translation, such as in the process where research findings created in academic settings are established as evidence and distributed for use in clinical practice, policy making, and health self-management. To date, it has been common for medical and public health institutions to have social media accounts for the dissemination of novel research findings and to facilitate conversations about these findings. However, recent events such as the transformation of the microblog Twitter to platform X have brought to light the need for the social media industry to exploit user data to generate revenue. In this viewpoint, it is argued that a redirection of social media use is required in the translation of knowledge to action in the fields of medicine and public health. A new kind of social internet is currently forming, known as the "fediverse," which denotes an ensemble of open social media that can communicate with each other while remaining independent platforms. In several countries, government institutions, universities, and newspapers use open social media to distribute information and enable discussions. These organizations control their own channels while being able to communicate with other platforms through open standards. Examples of medical knowledge translation via such open social media platforms, where users are less exposed to disinformation than in general platforms, are also beginning to appear. The current status of the social media industry calls for a broad discussion about the use of social technologies by health institutions involving researchers and health service practitioners, academic leaders, scientific publishers, social technology providers, policy makers, and the public. This debate should not primarily take place on social media platforms but rather at universities, in scientific journals, at public seminars, and other venues, allowing for the transparent and undisturbed communication and formation of opinions.

A peek into the room where it happens: Quantifying ABA's influence on public policy discussions

To maximize its influence, applied behavior analysis must both create solutions and shape public policy to implement those solutions at scale. From the perspective of data-driven decision making, it is illogical to talk about seeking public policy influence without consulting evidence showing when influence has been achieved. One relevant form of evidence is the attention that behavioral solutions receive in published discussions about policy issues, and here I show how much of this attention has been earned by articles published in Journal of Applied Behavior Analysis. I also propose using the same kind of data to support finer grained analyses focusing on specific behavior problems, specific types of interventions, and the research programs of individual investigators. Although this is far from a complete account of the influence of applied behavior analysis on policy, it is better to have data than none if the goal is to transform the quest for influence on policy from a matter of speculation and casual discussion into an evidence-based practice.

Evaluative altmetrics: is there evidence for its application to research evaluation?

Introduction

Altmetrics have been demonstrated as a promising tool for analyzing scientific communication on social media. Nevertheless, its application for research evaluation remains underdeveloped, despite the advancement of research in the study of diverse scientific interactions.

Methods

This paper develops a method for applying altmetrics in the evaluation of researchers, focusing on a case study of the Environment/Ecology ESI field publications by researchers at the University of Granada. We considered Twitter as a mirror of social attention, news outlets as media, and Wikipedia as educational, exploring mentions from these three sources and the associated actors in their respective media, contextualizing them using various metrics.

Results

Our analysis evaluated different dimensions such as the type of audience, local attention, engagement generated around the mention, and the profile of the actor. Our methodology effectively provided dashboards that gave a comprehensive view of the different instances of social attention at the author level.

Discussion

The use of altmetrics for research evaluation presents significant potential, as shown by our case study. While this is a novel method, our results suggest that altmetrics could provide valuable insights into the social attention that researchers garner. This can be an important tool for research evaluation, expanding our understanding beyond traditional metrics.

Slow, slow, quick, quick, slow: five altmetric sources observed over a decade show evolving trends, by research age, attention source maturity and open access status

The study of temporal trends in altmetrics is under-developed, and this multi-year observation study addresses some of the deficits in our understanding of altmetric behaviour over time. The attention surrounding research outputs, as partially captured by altmetrics, or alternative metrics, constitutes many varied forms of data. Over the years 2008–2013, a set of 7739 papers were sampled on six occasions. Five altmetric data sources were recorded (Twitter, Mendeley, News, Blogs and Policy) and analysed for temporal trends, with particular attention being paid to their Open Access status and discipline. Twitter attention both starts and ends quickly. Mendeley readers accumulate quickly, and continue to grow over the following years. News and blog attention is quick to start, although news attention persists over a longer timeframe. Citations in policy documents are slow to start, and are observed to be growing over a decade after publication. Over time, growth in Twitter activity is confirmed, alongside an apparent decline in blogging attention. Mendeley usage is observed to grow, but shows signs of recent decline. Policy attention is identified as the slowest form of impact studied by altmetrics, and one that strongly favours the Humanities and Social Sciences. The Open Access Altmetrics Advantage is seen to emerge and evolve over time, with each attention source showing different trends. The existence of late-emergent attention in all attention sources is confirmed.

Characteristics analysis and evaluation of discourse leading for academic journals: perspectives from multiple integration of altmetrics indicators and evaluation methods

Purpose

Under the background of open science, this paper integrates altmetrics data and combines multiple evaluation methods to analyze and evaluate the indicators' characteristics of discourse leading for academic journals, which is of great significance to enrich and improve the evaluation theory and indicator system of academic journals.

Design/methodology/approach

This paper obtained 795,631 citations and 10.3 million altmetrics indicators data for 126,424 published papers from 151 medicine, general and internal academic journals. In this paper, descriptive statistical analysis and distribution rules of evaluation indicators are first carried out at the macro level. The distribution characteristics of evaluation indicators under different international collaboration conditions are analyzed at the micro level. Second, according to the characteristics and connotation of the evaluation indicators, the evaluation indicator system is constructed. Third, correlation analysis, factor analysis, entropy weight method and TOPSIS method are adopted to evaluate and analyze the discourse leading in medicine, general and internal academic journals by integrating altmetrics. At the same time, this paper verifies the reliability of the evaluation results.

Findings

Six features of discourse leading integrated with altmetrics indicators are obtained. In the era of open science, online academic exchanges are becoming more and more popular. The evaluation activities based on altmetrics have fine-grained and procedural advantages. It is feasible and necessary to integrate altmetrics indicators and combine the advantages of multiple methods to evaluate the academic journals' discourse leading of which are in a diversified academic ecosystem.

Originality/value

This paper uses descriptive statistical analysis to analyze the distribution characteristics and distribution rules of discourse leading indicators of academic journals and to explore the availability of altmetrics indicators and the effectiveness of constructing an evaluation system. Then, combining the advantages of multiple evaluation methods, The author integrates altmetrics indicators to comprehensively evaluate the discourse leading of academic journals and verify the reliability of the evaluation results. This paper aims to provide references for enriching and improving the evaluation theory and indicator system of academic journals.

Are patents linked on Twitter? A case study of Google patents

This study attempts to analyze patents as cited/mentioned documents to better understand the interest, dissemination and engagement of these documents in social environments, laying the foundations for social media studies of patents (social Patentometrics).Particularly, this study aims to determine how patents are disseminated on Twitter by analyzing three elements: tweets linking to patents, users linking to patents, and patents linked from Twitter. To do this, all the tweets containing at least one link to a full-text patent available on Google Patents were collected and analyzed, yielding a total of 126,815 tweets (and 129,001 links) to 86,417 patents. The results evidence an increase of the number of linking tweets over the years, presumably due to the creation of a standardized patent URL ID and the integration of Google Patents and Google Scholar, which took place in 2015. The engagement achieved by these tweets is limited (80.2% of tweets did not attract likes) but increasing notably since 2018. Two super-publisher twitter bot accounts (dailypatent and uspatentbot) are responsible of 53.3% of all the linking tweets, while most accounts are sporadic users linking to patent as part of a conversation. The patents most tweeted are, by far, from United States (87.5% of all links to Google Patents), mainly due to the effect of the two super-publishers. The impact of patents in terms of the number of tweets linking to them is unrelated to their year of publication, status or number of patent citations received, while controversial and media topics might be more determinant factors. However, further research is needed to better understand the topics discussed around patents on Twitter, the users involved, and the metrics attained. Given the increasing number of linking users and linked patents, this study finds Twitter as a relevant source to measure patent-level metrics, shedding light on the impact and interest of patents by the broad public.

An Analysis of the 50 Most-Cited "Uveitis" Articles Published Between 2010-2020 From a Bibliographic and Altmetric Perspective

Purpose We aimed to evaluate the 50 most-cited articles on uveitis according to their Altmetric Attention Score (AAS) and additional metrics. Methods The Web of Science (WoS) core collection database was used in this study. The article and journal metrics and characteristics were examined. In addition, the effect of article and journal metrics on the AAS was examined with multivariate adaptive regression splines (MARS). Results The number of citations of the evaluated articles ranged from 670 to 90, and AASs ranged from 633 to 0. According to the MARS model, the importance scores of the predictors were as follows: article influence score (100%), immediacy index (77.74%), number of years since publication (57.79%), times cited in WoS (32.69%). We found that the trend of articles on uveitis was related to the "treatment category", namely, adalimumab. Second, the popular topic was uveitis caused by viruses. Conclusions We found that citation-based metrics and year of publication contributed to AAS. AAS appears to be inadequate in assessing the quality of articles. However, due to the electronic transformation of the publishing industry, it seems inevitable that altmetrics will become an additional supportive metric.

How relevant is climate change research for climate change policy? An empirical analysis based on Overton data

Climate change is an ongoing topic in nearly all areas of society since many years. A discussion of climate change without referring to scientific results is not imaginable. This is especially the case for policies since action on the macro scale is required to avoid costly consequences for society. In this study, we deal with the question of how research on climate change and policy are connected. In 2019, the new Overton database of policy documents was released including links to research papers that are cited by policy documents. The use of results and recommendations from research on climate change might be reflected in citations of scientific papers in policy documents. Although we suspect a lot of uncertainty related to the coverage of policy documents in Overton, there seems to be an impact of international climate policy cycles on policy document publication. We observe local peaks in climate policy documents around major decisions in international climate diplomacy. Our results point out that IGOs and think tanks–with a focus on climate change–have published more climate change policy documents than expected. We found that climate change papers that are cited in climate change policy documents received significantly more citations on average than climate change papers that are not cited in these documents. Both areas of society (science and policy) focus on similar climate change research fields: biology, earth sciences, engineering, and disease sciences. Based on these and other empirical results in this study, we propose a simple model of policy impact considering a chain of different document types: The chain starts with scientific assessment reports (systematic reviews) that lead via science communication documents (policy briefs, policy reports or plain language summaries) and government reports to legislative documents.

Digital artifacts reveal development and diffusion of climate research

Research for development organizations generate tremendous amount of accessible knowledge, but given their scale, time and resource constraints, the impact of outputs is not systematically analyzed. This is because traditional bibliometric analyses present limitations to synthesize accumulated knowledge and retrofitting indicators to historical outputs. To address these shortcomings, this study proposes an integrated, web-based approach to systematically analyze the production and diffusion of knowledge from large-scale research programs, using climate research of the International Maize and Wheat Improvement Center (CIMMYT) as a case study. Our analytical framework employs text mining, social network analysis and hyperlink analysis to an unstructured mass of publicly available digital artifacts such as institutional repositories, citation databases, and social media to uncover narratives, dynamics, and relationships. Findings show CIMMYT’s climate research is strongly incorporated into a holistic systems approach and that the institution is actively engaged in knowledge exchanges with key actors from the scientific, development and public policy communities. The proposed analytical framework establishes an effective approach for research for development organizations to leverage existing online data sources to assess the extent of their knowledge production, dissemination, and reach.

User engagement with scholarly tweets of scientific papers: a large-scale and cross-disciplinary analysis

This study investigates the extent to which scholarly tweets of scientific papers are engaged with by Twitter users through four types of user engagement behaviors, i.e., liking, retweeting, quoting, and replying. Based on a sample consisting of 7 million scholarly tweets of Web of Science papers, our results show that likes is the most prevalent engagement metric, covering 44% of scholarly tweets, followed by retweets (36%), whereas quotes and replies are only present for 9% and 7% of all scholarly tweets, respectively. From a disciplinary point of view, scholarly tweets in the field of Social Sciences and Humanities are more likely to trigger user engagement over other subject fields. The presence of user engagement is more associated with other Twitter-based factors (e.g., number of mentioned users in tweets and number of followers of users) than with science-based factors (e.g., citations and Mendeley readers of tweeted papers). Building on these findings, this study sheds light on the possibility to apply user engagement metrics in measuring deeper levels of Twitter reception of scholarly information.

Association Between Immediacy of Citations and Altmetrics in COVID-19 Research by Artificial Neural Networks

OBJECTIVES

Both citations and Altmetrics are indexes of influence of a publication, potentially useful, but to what extent that the professional-academic citation and media-dominated Altmetrics are consistent with each other is a topic worthy of being investigated. The objective is to show their correlation.

METHODS

DOI and citation information of coronavirus disease 2019 (COVID-19) researches were obtained from the Web of Science, its Altmetric indicators were collected from the Altmetrics. Correlation between the immediacy of citation and Altmetrics of COVID-19 research was studied by artificial neural networks.

RESULTS

Pearson coefficients are 0.962, 0.254, 0.222, 0.239, 0.363, 0.218, 0.136, 0.134, and 0.505 (P < 0.01) for dimensions citation, attention score, journal impact factor, news, blogs, Twitter, Facebook, video, and Mendeley correlated with the SCI citation, respectively. The citations from the Web of Science and that from the Altmetrics have deviance large enough in the current. Altmetric score is not precise to describe the immediacy of citations of academic publication in COVID-19 research.

CONCLUSIONS

The effects of news, blogs, Twitter, Facebook, video, and Mendeley on SCI citations are similar to that of the journal impact factor. This paper performs a pioneer study for investigating the role of academic topics across Altmetric sources on the dissemination of scholarly publications.

The nature of rapid response to COVID-19 in Latin America: an examination of Argentina, Brazil, Chile, Colombia and Mexico

Purpose

The coronavirus-19 (COVID-19) pandemic mobilized the international scientific community in the search for its cure and containment. The purpose of this paper is to examine the nature of the rapid response to the COVID-19 of the scientific community in selected Latin American countries (Argentina, Brazil, Chile, Colombia and Mexico) in the period running from January to August 2020. Rapid response is reconceptualized from its original meaning in health policy, as the swift mobilization of existing scientific resources to address an emergency (DeVita et al., 2017).

Design/methodology/approach

The paper explores the rapid response of the Argentinian, Brazilian, Chilean, Colombian and Mexican scientific communities from the perspective of bibliometric and altmetric data. The authors will examine scientific publications indexed to the Web of Science (WoS) dealing with COVID-19. Besides patterns of scientific output and impact as measured by citations, the authors complement the analysis with altmetric analysis. The aim is to verify whether or not factors that explain the extent of scientific impact can also be identified with respect to the wider impact made evident by altmetric indicators (Haustein, 2016).

Findings

The authors identified a somewhat limited response of the Argentinian, Brazilian, Chilean, Colombian and Mexican scientific communities to COVID-19 in terms of quantity of publications. The authorship of publications in the topic of COVID-19 was associated with authorship of publications dealing with locally relevant diseases. Some factors appear to contribute to visibility of scientific outputs. Papers that involved wider international collaborations and authors with previous publications in arboviruses were associated with higher levels of citations. Previous work on arbovirus was also associated with higher altmetric attention. The country of origin of authors exerted a positive effect on altmetric indicators.

Research limitations/implications

A limitation in the analysis is that, due to the nature of the data source (WoS), the authors were unable to verify the career status and the productivity of the authors in the sample. Nonetheless, the results appear to suggest that there is some overlapping in authors conducting research in Arboviruses and COVID-19. Career status and productivity should be the focus of future research.

Practical implications

In the context of countries with limited scientific resources, like the ones investigated in our Latin American sample, previous efforts in the study of locally relevant diseases may contribute to the creation of an expertise that can be applied when a health emergency brings about a novel disease.

Originality/value

The originality of the paper rests on the fact that the authors identified that previous work on arbovirus contributed to the scientific visibility of publications on COVID-19.