Scholarly Metrics – DigitalKoans

“Open Infrastructures for Responsible Research Assessment: the CoARA Working Group publishes Its First Report”

The OI4RRA report stresses that transitioning to OIs requires institutions and stakeholders to identify the advantages that OIs offer in comparison with closed systems. These can be summarised in four key contributions.

In contrast to the traditional focus on publications and journal-based metrics, OIs support the consideration of a broad range of scholarly contributions in research evaluations.

OIs have the ability to integrate data-driven indicators with the nuance of contextual and narrative based information.

Thirdly, interoperability paired with community-driven governance for evaluations promote the uptake of best practices and foster trust.

Lastly, an emphasis on transparent data automation streamlines workflows, allowing researchers to devote more time to actual research.

https://tinyurl.com/vasmmrsh

Open Infrastructures for Responsible Research Assessment: Principles and Framework

"Clarivate Identifies Top 50 Universities Powering Global Innovation"

Drawing on a host of Clarivate data – from the Web of Science to Derwent World Patent Index, and Derwent Patents Citation Index – the report highlights how knowledge flows between academia and industry across countries and regions, underscoring the global nature of innovation. The study identifies the top 50 universities named on the academic papers that received the highest number of citations from patents granted to the companies and organizations on the Top 100 Global Innovators 2024 list.

Key findings include:

The top 50 universities powering global innovation are distributed across eleven countries or regions – from Canada to South Korea

U.S. universities such as Harvard, Stanford, and the Massachusetts Institute of Technology (MIT) dominate. Harvard leads with its high volume of research outputs, but MIT’s smaller, yet highly impactful publications highlight its exceptional ability to translate research into groundbreaking innovations

Strong regional citation patterns emerge, with companies in Eastern Asia and Europe heavily relying on local academic research, while U.S. research is the most globally cited

The United Kingdom demonstrates particularly diverse international influence, with its research often serving as a bridge across regions.

Five organizations – Roche, Johnson & Johnson, Centre National de la Recherche Scientifique (CNRS), Samsung Electronics, and Siemens – account for over half (51%) of citations from top innovations to academic research

https://tinyurl.com/yc4nea6k

"An Analysis of the Effects of Sharing Research Data, Code, and Preprints on Citations"

In this study, we investigate whether adopting one or more Open Science practices leads to significantly higher citations for an associated publication, which is one form of academic impact. We use a novel dataset known as Open Science Indicators, produced by PLOS and DataSeer, which includes all PLOS publications from 2018 to 2023 as well as a comparison group sampled from the PMC Open Access Subset. In total, we analyze circa 122’000 publications. We calculate publication and author-level citation indicators and use a broad set of control variables to isolate the effect of Open Science Indicators on received citations. We show that Open Science practices are adopted to different degrees across scientific disciplines. We find that the early release of a publication as a preprint correlates with a significant positive citation advantage of about 20.2% (±.7) on average. We also find that sharing data in an online repository correlates with a smaller yet still positive citation advantage of 4.3% (±.8) on average. However, we do not find a significant citation advantage for sharing code. Further research is needed on additional or alternative measures of impact beyond citations. Our results are likely to be of interest to researchers, as well as publishers, research funders, and policymakers.

https://doi.org/10.1371/journal.pone.0311493

"Impact Factor Does Not Predict Long-Term Article Impact across 15 Journals"

Authors who publish in journals with higher impact factors are deemed to contribute more to their discipline. However, the impact factor of a journal does not indicate how long a specific article stays in the scientific discourse, and metrics that measure the length of time articles within a journal continue to be cited are not typically used. We examined citations of 443,732 research articles [786,064 total] between 1980 and 2020 across 15 journals. We explored the range of longevity values found across different journals as well as the relationship between impact factor and longevity. We found no relationship between impact factor and longevity, indicating that immediate attention to an article is not correlated with longer-term impact. . . .

For early-career scholars, the implications of citation longevity can be meaningful. Our data suggest that a new faculty member publishing primarily in strong society journals has yet to reach their full impact by mid-career milestones such as applying for tenure and promotion. The total contribution of the work to the field will likely not be seen until after their career is finished. . . .

The results presented here have important implications for journal selection and evaluation of science academics. For example, early career researchers may benefit from publishing in lower-impact, higher-longevity journals because their work may become classic within their field when they reach full promotion. Additionally, hiring and promotion committees should consider giving journals with higher longevity scores more weight among early career researchers, as these works can potentially impact departmental rankings over the long run. Furthermore, funding agencies and university review committees could benefit from a holistic analysis of academic productivity by examining article and journal performance metrics over time along with traditional indicators, such as altmetrics (Fortin et al., 2021), impact factor, and total citations.

https://doi.org/10.1016/j.dim.2024.100079

"Women and Men in Library and Information Science Scholarship: Authorship Trends from 2003 to 2021"

Library and information science (LIS) has long consisted of more women than men, at least in sheer numbers of library employees, but men are the primary authors of library literature. This study explores LIS literature published between 2003 and 2021 to identify if there are differences in the publishing patterns of women and men. The authors used content analysis to code the entire sample to identify overall subject trends after authors were categorized as women or men by mainly automated methods, using two R packages, genderize and ssa. The results show that there are overall inequities when compared to the profession as whole between the publishing rates of women and men in LIS, as well as differences in publication patterns by subjects and within specific journals. Shifts in subjects over the period under investigation did not increase the percentage of women publishing in the selected LIS journals. The authors conclude more research needs to be conducted to determine the cause of inequities in publishing not just among women and men, but all underrepresented voices in LIS.

https://doi.org/10.1016/j.acalib.2024.102939

"Evaluating Open Access Advantages for Citations and Altmetrics (2011-21): A Dynamic and Evolving Relationship"

Differences between the impacts of Open Access (OA) and non-OA research have been observed over a wide range of citation and altmetric indicators, usually finding an Open Access Advantage (OAA) within specific fields. However, science-wide analyses covering multiple years, indicators and disciplines are lacking. Using citation counts and six altmetrics for 38.7M articles published 2011-21, we compare OA and non-OA papers. The results show that there is no universal OAA across all disciplines or impact indicators: the OAA for citations tends to be lower for more recent papers, whereas the OAAs for news, blogs and Twitter are consistent across years and unrelated to volume of OA publications, whereas the OAAs for Wikipedia, patents and policy citations are more complex. These results support different hypotheses for different subjects and indicators. The evidence is consistent with OA accelerating research impact in the Medical & Health Sciences, Life Sciences and the Humanities; that increased visibility or discoverability is a factor in promoting the translation of research into socio-economic impact; and that OA is a factor in growing online engagement with research in some disciplines. . . .

Furthermore, the advantages of OA are not evenly distributed: while there is evidence that some fields (Medical & Health Science, Life Sciences, Humanities) are being strengthened by OA adoption, there is the possibility that others (Social Sciences) are being weakened. Additionally, it is notable that while some fields appear to have their visibility and socio-economic impact boosted by their OA status, others (Humanities, Social Sciences) are not similarly benefited.

https://arxiv.org/abs/2406.10535

"Exploring the Relationship between Traditional Bibliometrics and Altmetric Scores in the Primary Care Literature"

There is some evidence that Altmetric scores correlate with citations in medical research, but this is not consistent across different specialties.

No previous studies have examined the association between Altmetric score and citation amongst primary care research journals.

Using correlation coefficients and log–log linear regression modelling, this study found a relationship between Altmetric score and citations.

A 10% increase in Altmetric score was associated with a 1.68% (95% CI: 0.87%–2.50%) increase in citations.

https://doi.org/10.1002/leap.1584

Paywall: "Does Research Funding, Open Access Availability, and Collaboration in Research Influence Citation Impact? An Analysis of Neurotechnology Research"

The United States Department of Health and Human Services remains at the top by contributing funding to 7.46% of research papers in the field of Neurotechnology research. Statistical tests confirmed significant correlations between research funding, collaboration, and research availability mode with citation impact. Positive correlations were identified between research funding and collaboration, while open access availability showed a negative correlation with citation impact.

https://doi.org/10.1080/15424065.2024.2350377

"Amplifying Academic Research through YouTube: Engagement Metrics as Predictors of Citation Impact"

The preliminary findings from the linear regression analysis (Table 1) suggest a meaningful relationship between the online engagement metrics of videos on YouTube and the academic impact of the publications referenced within these videos. Specifically, the analysis found positive correlations with the citation impact for three key metrics: the number of videos referencing publications, the ratio of likes to dislikes on videos, and the number of comments containing references to other publications. The positive correlation indicates a sort of selective amplification process. Publications mentioned in videos that garner attention in the form of likes and active discussion in comments are likely being selectively chosen for their relevance or quality. This selection process by content creators and the subsequent engagement by viewers may serve as an “informal peer review”, signaling the value and impact of the research. The findings suggest that social media, particularly YouTube in this context, acts as a filter that potentially can highlight the visibility of impactful research.

https://arxiv.org/abs/2405.12734

"Relationships between Expert Ratings of Business/Economics Journals and Key Citation Metrics: The Impact of Size-Independence, Citing-Journal Weighting, and Subject-Area Normalization"

This study uses data for >3300 business and economics journals to explore the relationships between 5 subjective (expert) journal ratings and 10 citation metrics including 5IF (5-year Impact Factor), Article Influence (AI) score, CiteScore, Eigenfactor, Impact per Publication, SJR, and SNIP. Overall, AI and SJR are the citation metrics most closely related to the expert journal ratings. . . . These results, which are consistent across the 5 expert ratings, suggest that evaluators consider the average impact of an article in each journal rather than the total impact of the journal as a whole, that they give more credit for citations in high-impact journals than for citations in lesser journals, and that they assess each journal’s relative standing within its own field or subfield rather than its broader scholarly impact.

https://doi.org/10.1016/j.acalib.2024.102882

"Different Open Access Routes, Varying Societal Impacts: Evidence from the Royal Society Biological Journals"

In this article, we explore different OA routes (i.e., gold OA, hybrid OA, and bronze OA) and their varying effects on multiple types of societal impacts (i.e., social media and web) by using the case of four biological journals founded by the Royal Society. The results show that (1) gold OA is significantly and positively related to social media indicators (Twitter counts and Facebook counts), but significantly and negatively associated with web indicators (Blog counts and News counts); (2) hybrid OA has a significant and positive effect on both social media and web indicators; and (3) bronze OA is significantly and positively associated with social media indicators, but it turns to be negative albeit nonsignificant for web indicators.

https://doi.org/10.1007/s11192-024-05032-0

AI-native Platform: "Reimagining Research Impact: Introducing Web of Science Research Intelligence"

Currently being developed in partnership with leading academic institutions, Web of Science Research Intelligence is an AI-native platform that embodies a vision centered on three pillars: unification, innovation and impact. It seamlessly integrates funding data with research outputs that include publications, patents, conference proceedings, books, policy documents and more. Based on these data, the platform identifies relevant funding opportunities within emerging research areas, equipping institutions and researchers to innovate.

A conversational assistant powered by generative AI enables all users to gain insights and create qualitative narratives for more balanced impact assessment, from data scientists to those with limited analysis experience.

Tailored recommendations for collaboration and funding help early career researchers build their networks and all researchers position themselves to win.

A new framework for measuring societal impact beyond traditional citation metrics will empower researchers and institutions to showcase the broader impacts of their work.

https://tinyurl.com/2zdshm6b

Next Generation Metrics for Scientific and Scholarly Research in Europe

The field of evaluating academic activities is vast, complex, and highly dynamic, as are the roles of any data and indicators used to support these evaluations This Next Generation Metrics for Scientific and Scholarly Research in Europe paper, explores how universities can and should use currently available metrics and data to assess their research evaluation processes, in conjunction with qualitative expertise and information.

The authors have chosen to focus on the aspect of academic evaluation that shows great potential for significant advancements in the coming years: the use and advancement of next-generation metrics for responsible research evaluation, encompassing open science, societal impact, and innovation.

The paper aims to support universities in shaping their metric policies in alignment with their own missions, rather than relying solely on standard metrics and data availability. The paper furthermore intends to serve as a framework for universities to determine priorities to work on in specific domains for the application of contextually relevant indicators and metrics.

The authors place strong emphasis on the reuse of existing expertise on metrics as well as on collaboration, both among universities and between universities and funding agencies to achieve these goals.

https://doi.org/10.5281/zenodo.11123148

Paywall: "Open Peer Review Correlates with Altmetrics but Not with Citations: Evidence from Nature Communications and PLoS One"

The analysis reveals articles subjected to OPR [Open Peer Review] have no obvious advantage in citations but a notable higher score in altmetrics. The distribution of data variation across most disciplines, displaying a statistically significant difference between OPR and non-OPR, mirrors the overall trend. Two potential explanations for the disparity in OPR’s impact on citations compared to altmetrics are proposed. The first relates to the quality heterogeneity between OPR and non-OPR research, while the second is related to the diverse authors citing and mentioning articles in distinct communities.

https://doi.org/10.1016/j.joi.2024.101540

"An Analysis of the Effects of Sharing Research Data, Code, and Preprints on Citations"

In this study, we investigate whether adopting one or more Open Science practices leads to significantly higher citations for an associated publication, which is one form of academic impact. We use a novel dataset known as Open Science Indicators, produced by PLOS and DataSeer, which includes all PLOS publications from 2018 to 2023 as well as a comparison group sampled from the PMC Open Access Subset. In total, we analyze circa 122’000 publications. We calculate publication and author-level citation indicators and use a broad set of control variables to isolate the effect of Open Science Indicators on received citations. We show that Open Science practices are adopted to different degrees across scientific disciplines. We find that the early release of a publication as a preprint correlates with a significant positive citation advantage of about 20.2% on average. We also find that sharing data in an online repository correlates with a smaller yet still positive citation advantage of 4.3% on average. However, we do not find a significant citation advantage for sharing code.

https://arxiv.org/abs/2404.16171

"Forensic Scientometrics — An Emerging Discipline to Protect the Scholarly Record"

Forensic Scientometrics (FoSci) is emerging as a vital discipline at the intersection of scientific integrity and security. Scholarship and scholarly communication are critical for maintaining scientific integrity, influencing public trust in science, health, technology, policy, and law. Yet, these foundations are threatened by the misuse of scientific research for personal, commercial, ideological, and geopolitical gains, including questionable practices and misconduct. The rise of paper mills and predatory publishers, along with ideological and geopolitical motivations, undermines academic integrity. This field pioneers the integration of traditional scientometric methods with ethics to address pressing challenges in research integrity and security, crucial in an era of heightened scrutiny over science’s reliability. FoSci’s development signifies a collective commitment to maintaining scientific trust, marked by a call for official recognition and support from stakeholders across the scientific ecosystem.

https://arxiv.org/abs/2404.00478

"Unleashing the Power of AI. A Systematic Review of Cutting-Edge Techniques in AI-Enhanced Scientometrics, Webometrics, and Bibliometrics"

Findings: (i) Regarding scientometrics, the application of AI yields various distinct advantages, such as conducting analyses of publications, citations, research impact prediction, collaboration, research trend analysis, and knowledge mapping, in a more objective and reliable framework. (ii) In terms of webometrics, AI algorithms are able to enhance web crawling and data collection, web link analysis, web content analysis, social media analysis, web impact analysis, and recommender systems. (iii) Moreover, automation of data collection, analysis of citations, disambiguation of authors, analysis of co-authorship networks, assessment of research impact, text mining, and recommender systems are considered as the potential of AI integration in the field of bibliometrics.

https://arxiv.org/abs/2403.18838

"Controlled Experiment Finds No Detectable Citation Bump from Twitter Promotion"

Multiple studies across a variety of scientific disciplines have shown that the number of times that a paper is shared on Twitter (now called X) is correlated with the number of citations that paper receives. However, these studies were not designed to answer whether tweeting about scientific papers causes an increase in citations, or whether they were simply highlighting that some papers have higher relevance, importance or quality and are therefore both tweeted about more and cited more. The authors of this study are leading science communicators on Twitter from several life science disciplines, with substantially higher follower counts than the average scientist, making us uniquely placed to address this question. We conducted a three-year-long controlled experiment, randomly selecting five articles published in the same month and journal, and randomly tweeting one while retaining the others as controls. This process was repeated for 10 articles from each of 11 journals, recording Altmetric scores, number of tweets, and citation counts before and after tweeting. Randomization tests revealed that tweeted articles were downloaded 2.6–3.9 times more often than controls immediately after tweeting, and retained significantly higher Altmetric scores (+81%) and number of tweets (+105%) three years after tweeting. However, while some tweeted papers were cited more than their respective control papers published in the same journal and month, the overall increase in citation counts after three years (+7% for Web of Science and +12% for Google Scholar) was not statistically significant (p > 0.15). Therefore while discussing science on social media has many professional and societal benefits (and has been a lot of fun), increasing the citation rate of a scientist’s papers is likely not among them.

https://doi.org/10.1371/journal.pone.0292201

"OurResearch Receives $7.5M grant from Arcadia to Establish OpenAlex, a Milestone Development for Open Science"

OurResearch is proud to announce a $7.5M grant from Arcadia, to establish a sustainable and completely open index of the world’s research ecosystem. With this 5-year grant, OurResearch expands their open science ambitions to replace paywalled knowledge graphs with OpenAlex. . . .

OpenAlex indexes more than twice as many scholarly works as the leading proprietary products and the entirety of the knowledge graph and its source code are openly licensed and freely available through data snapshots, an easy to use API, and a nascent user interface. . . .

Development of OpenAlex started only two years ago and it already serves 115M API calls per month; underlies a major university ranking; is displacing proprietary products at Universities; and has established partnerships with national governments. We are excited by these early successes of OpenAlex and its promise to revolutionize scholarly communication and democratize the world’s research.

You can use OpenAlex‘s Author Profile Change Request Form, to correct certain types of errors about your publications, such as "My work has been incorrectly attributed to another author."

There is also a Submit a Request form, but it is not clear if this can be used to correct citation count or other types of errors not covered by the above form.

https://tinyurl.com/3396s27m

"Information Accessibility and Knowledge Creation: The Impact of Google’s Withdrawal from China on Scientific Research"

How important is Google for scientific research? This paper exploits the exogenous shock represented by Google’s sudden withdrawal of its services from mainland China to assess the importance of access to information for the knowledge production function of scientific scholars in the field of economics. For economists, a type of scholar with a simple knowledge production function, results from difference-in-difference analyses, which compare their scientific output to scholars located in the neighbouring regions, show that the scientific productivity declines by about 28% in volume and 30% in terms of citations. These results are consistent with the view that information accessibility is an important driver of scientific progress. Considering that the negative effect of the shock is stronger for top scholars located in China, Google’s sudden exit bears the risk that researchers lose touch with the research frontier and persistently lag behind their foreign peers.

https://doi.org/10.1080/13662716.2023.2298293

"Citation Amnesia: NLP and Other Academic Fields Are in a Citation Age Recession"

This study examines the tendency to cite older work across 20 fields of study over 43 years (1980–2023). . . . Our analysis, based on a dataset of approximately 240 million papers, reveals a broader scientific trend: many fields have markedly declined in citing older works (e.g., psychology, computer science). . . . Our results suggest that citing more recent works is not directly driven by the growth in publication rates. . . even when controlling for an increase in the volume of papers. Our findings raise questions about the scientific community’s engagement with past literature, particularly for NLP, and the potential consequences of neglecting older but relevant research.

https://arxiv.org/abs/2402.12046

"Can ChatGPT Be Used to Predict Citation Counts, Readership, and Social Media Interaction? An Exploration among 2222 Scientific Abstracts"

This study explores the potential of ChatGPT, a large language model, in scientometrics by assessing its ability to predict citation counts, Mendeley readers, and social media engagement. In this study, 2222 abstracts from PLOS ONE articles published during the initial months of 2022 were analyzed using ChatGPT-4, which used a set of 60 criteria to assess each abstract. Using a principal component analysis, three components were identified: Quality and Reliability, Accessibility and Understandability, and Novelty and Engagement. The Accessibility and Understandability of the abstracts correlated with higher Mendeley readership, while Novelty and Engagement and Accessibility and Understandability were linked to citation counts (Dimensions, Scopus, Google Scholar) and social media attention. Quality and Reliability showed minimal correlation with citation and altmetrics outcomes. Finally, it was found that the predictive correlations of ChatGPT-based assessments surpassed traditional readability metrics. The findings highlight the potential of large language models in scientometrics and possibly pave the way for AI-assisted peer review.

https://doi.org/10.1007/s11192-024-04939-y

"Google Scholar is Manipulatable"

Citations are widely considered in scientists’ evaluation. As such, scientists may be incentivized to inflate their citation counts. While previous literature has examined self-citations and citation cartels, it remains unclear whether scientists can purchase citations. Here, we compile a dataset of ~1.6 million profiles on Google Scholar to examine instances of citation fraud on the platform. We survey faculty at highly-ranked universities, and confirm that Google Scholar is widely used when evaluating scientists. Intrigued by a citation-boosting service that we unravelled during our investigation, we contacted the service while undercover as a fictional author, and managed to purchase 50 citations. These findings provide conclusive evidence that citations can be bought in bulk, and highlight the need to look beyond citation counts.

https://arxiv.org/abs/2402.04607

"Is Gold Open Access Helpful for Academic Purification? A Causal Inference Analysis Based on Retracted Articles in Biochemistry"

The results showed that compared to non-OA, Gold OA is advantageous in reducing the retraction time of flawed articles, but does not demonstrate a significant advantage in reducing citations after retraction. This indicates that Gold OA may help expedite the detection and retraction of flawed articles, ultimately promoting the practice of responsible research.

https://doi.org/10.1016/j.ipm.2023.103640

"Are Open Bibliometric Data Sources Better than Proprietary Ones?"

The authors concluded that the resulting data based on open bibliometric sources was more comprehensive and of better quality than the data based on sources provided by the commercial provider. In addition, the use of open source data allows scidecode to comply with the requirement set by cOAlition S to openly licence their results, which would not necessarily be the case if they had used a commercial provider.

http://tinyurl.com/2btc8a76