"Bibliometrics Methods in Detecting Citations to Questionable Journals"


This paper intends to analyse whether journals that had been removed from the Directory of Open Access Journals (DOAJ) in 2018 due to suspected misconduct were cited within journals indexed in the Scopus database. Our analysis showed that Scopus contained over 15 thousand references to the removed journals identified.

https://doi.org/10.1016/j.acalib.2023.102749

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Requires Registration: "Clarivate Report Urges Shift from Single Metrics to Visual Research Profiles"


The report focuses on four key areas:

  • Individuals and their publications: The issue of excessive self-citation in research publications is addressed, with identification of outliers following examination of the distinctive patterns of self-citation observed among Highly Cited Researchers, while considering variations in citation rates between fields.
  • Future research trends: Research Fronts identifies current areas of research attention by analyzing frequently cited, recent papers that cluster together, providing valuable insights for research planning, resource management and policy decisions.
  • Journals and their characteristics: The profile and value of a journal in the Web of Science is more than its Journal Impact Factor. We explore how the indicator of national orientation (INO) offers new perspectives on journals, helping researchers choose the best venues for their papers.
  • Influence of international collaboration: Simple metrics mask the influence of well-cited, internationally co-authored papers, so cannot be properly used to assess them. Collaborative Citation Impact (Collab-CNCI) allows deconstruction of impact, enabling better evaluation of domestic and international activity.

https://tinyurl.com/4vetr6px

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"Factors Affecting Publication Impact and Citation Trends Over Time"


Based on the results, researchers should seek out grant funding and generously incorporate literature into their co-authored publications to increase their publications’ potential for future impact. These factors may influence article quality, resulting in more citations over time. Further research is needed to better understand their influence and the influence of other factors.

https://doi.org/10.18438/eblip30206

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"Evaluating the Efficacy of ChatGPT-4 in Providing Scientific References across Diverse Disciplines"


This work conducts a comprehensive exploration into the proficiency of OpenAI’s ChatGPT-4 in sourcing scientific references within an array of research disciplines. Our in-depth analysis encompasses a wide scope of fields including Computer Science (CS), Mechanical Engineering (ME), Electrical Engineering (EE), Biomedical Engineering (BME), and Medicine, as well as their more specialized sub-domains. Our empirical findings indicate a significant variance in ChatGPT-4’s performance across these disciplines. Notably, the validity rate of suggested articles in CS, BME, and Medicine surpasses 65%, whereas in the realms of ME and EE, the model fails to verify any article as valid. Further, in the context of retrieving articles pertinent to niche research topics, ChatGPT-4 tends to yield references that align with the broader thematic areas as opposed to the narrowly defined topics of interest. This observed disparity underscores the pronounced variability in accuracy across diverse research fields, indicating the potential requirement for model refinement to enhance its functionality in academic research. Our investigation offers valuable insights into the current capacities and limitations of AI-powered tools in scholarly research, thereby emphasizing the indispensable role of human oversight and rigorous validation in leveraging such models for academic pursuits.

https://arxiv.org/abs/2306.09914v1

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"Can Open Access Increase LIS Research’s Policy Impact? Using Regression Analysis and Causal Inference"


The relationship between open access and academic impact (usually measured as citations received from academic publications) has been extensively studied but remains a very controversial topic. However, the effect of open access on policy impact (measured as citations received from policy documents) is still unknown. The purpose of this study was to examine the effect of open access on the policy impact, which might initiate a new controversial topic. . . . Linear regression models, logit regression models, four other matching methods, open access status provided by different databases, and different sizes of data samples were used to check the robustness of the main results. This study revealed that open access had significant and positive effects on the policy impact.

https://doi.org/10.1007/s11192-023-04750-1

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"How and Why Do Researchers Reference Data? A Study of Rhetorical Features and Functions of Data References in Academic Articles"


Data reuse is a common practice in the social sciences. While published data play an essential role in the production of social science research, they are not consistently cited, which makes it difficult to assess their full scholarly impact and give credit to the original data producers. Furthermore, it can be challenging to understand researchers’ motivations for referencing data. Like references to academic literature, data references perform various rhetorical functions, such as paying homage, signaling disagreement, or drawing comparisons. This paper studies how and why researchers reference social science data in their academic writing. We develop a typology to model relationships between the entities that anchor data references, along with their features (access, actions, locations, styles, types) and functions (critique, describe, illustrate, interact, legitimize). We illustrate the use of the typology by coding multidisciplinary research articles (n = 30) referencing social science data archived at the Inter-university Consortium for Political and Social Research (ICPSR). We show how our typology captures researchers’ interactions with data and purposes for referencing data. Our typology provides a systematic way to document and analyze researchers’ narratives about data use, extending our ability to give credit to data that support research.

https://doi.org/10.5334/dsj-2023-010

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"No Deal: German Researchers’ Publishing and Citing Behaviours after Big Deal Negotiations with Elsevier"


In 2014, a union of German research organisations established Projekt DEAL, a national-level project to negotiate licensing agreements with large scientific publishers. Negotiations between DEAL and Elsevier began in 2016, and broke down without a successful agreement in 2018; in this time, around 200 German research institutions cancelled their license agreements with Elsevier, leading Elsevier to restrict journal access at those institutions. We investigated the effect on researchers’ publishing and citing behaviours from a bibliometric perspective, using a dataset of ~400,000 articles published by researchers at DEAL institutions between 2012–2020. We further investigated these effects with respect to the timing of contract cancellations, research disciplines, collaboration patterns, and article open-access status. We find evidence for a decrease in Elsevier’s market share of articles from DEAL institutions, with the largest year-on-year market share decreases occuring from 2018 to 2020 following the implementation of access restrictions. We also observe year-on-year decreases in the proportion of citations, although the decrease is smaller. We conclude that negotiations with Elsevier and access restrictions have led to some reduced willingness to publish in Elsevier journals, but that researchers are not strongly affected in their ability to cite Elsevier articles, implying that researchers use other methods to access scientific literature.

https://doi.org/10.1162/qss_a_00255

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"Which Factors are Associated with Open Access Publishing? A Springer Nature Case Study"


Open Access (OA) facilitates access to articles. But, authors or funders often must pay the publishing costs preventing authors who do not receive financial support from participating in OA publishing and citation advantage for OA articles. OA may exacerbate existing inequalities in the publication system rather than overcome them. To investigate this, we studied 522,411 articles published by Springer Nature. Employing correlation and regression analyses, we describe the relationship between authors affiliated with countries from different income levels, their choice of publishing model, and the citation impact of their papers. A machine learning classification method helped us to explore the importance of different features in predicting the publishing model. The results show that authors eligible for APC waivers publish more in gold-OA journals than other authors. In contrast, authors eligible for an APC discount have the lowest ratio of OA publications, leading to the assumption that this discount insufficiently motivates authors to publish in gold-OA journals. We found a strong correlation between the journal rank and the publishing model in gold-OA journals, whereas the OA option is mostly avoided in hybrid journals. Also, results show the countries’ income level, seniority, and experience with OA publications as the most predictive factors for OA publishing in hybrid journals.

https://doi.org/10.1162/qss_a_00253

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"How Related are Journal Impact and Research Impact? "


The dominance of journal impact factors as a proxy for research quality and impact has been challenged, to the extent that academic impacts are being eroded from definitions of research impact all together. It’s one of many bandwagons that seem logical to jump on, but which don’t necessarily hold up under scrutiny. The publishing community needs to demonstrate that it is a following wind, not a headwind.

http://bit.ly/3GBv0kS

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"What Does Open Peer Review Bring to Scientific Articles? Evidence from PLOS Journals"


This study examined the impact of open peer review (OPR) on the usage and citations of scientific articles using a dataset of 6441 articles published in six Public Library of Science (PLoS) journals in 2020–2021. We compared OPR articles with their non-OPR counterparts in the same journal to determine whether OPR increased the visibility and citations of the articles. Our results demonstrated a positive association between OPR and higher article page views, saving, sharing, and a greater HTML to PDF conversion rate. However, we also found that OPR articles had a lower PDF to citations conversion rate compared to non-OPR articles.

https://doi.org/10.1007/s11192-023-04683-9

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"Towards a Better Understanding of Facebook Altmetrics in LIS Field: Assessing the Characteristics of Involved Paper, User and Post"


These findings indicate that Facebook mentions to LIS papers mainly reflect the institutional level advocacy and attention, with low level of engagement, and could be influenced by several features including collaborative patterns and research topics.

https://doi.org/10.1145/2756406.2756913

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"Fast-Growing Open-Access Journals Stripped of Coveted Impact Factors"


Nearly two dozen journals from two of the fastest growing open-access publishers, including one of the world’s largest journals by volume, will no longer receive a key scholarly imprimatur. On 20 March, the Web of Science database said it delisted the journals along with dozens of others, stripping them of an impact factor, the citation-based measure of quality that, although controversial, carries weight with authors and institutions. . . . Clarivate initially did not name any of the delisted journals or provide specific reasons. But it confirmed to Science the identities of 19 Hindawi journals and two MDPI titles after reports circulated about their removals.

https://bit.ly/3Kjx1ET

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"Hybrid Gold Open Access Citation Advantage in Clinical Medicine: Analysis of Hybrid Journals in the Web of Science"


Biomedical fields have seen a remarkable increase in hybrid Gold open access articles. However, it is uncertain whether the hybrid Gold open access option contributes to a citation advantage, an increase in the citations of articles made immediately available as open access regardless of the article’s quality or whether it involves a trending topic of discussion. This study aimed to compare the citation counts of hybrid Gold open access articles to subscription articles published in hybrid journals. The study aimed to ascertain if hybrid Gold open access publications yield an advantage in terms of citations. This cross-sectional study included the list of hybrid journals under 59 categories in the "Clinical Medicine" group from Clarivate’s Journal Citation Reports (JCR) during 2018–2021. The number of citable items with ‘Gold Open Access’ and ‘Subscription and Free to Read’ in each journal, as well as the number of citations of those citable items, were extracted from JCR. A hybrid Gold open access citation advantage was computed by dividing the number of citations per citable item with hybrid Gold open access by the number of citations per citable item with a subscription. A total of 498, 636, 1009, and 1328 hybrid journals in the 2018 JCR, 2019 JCR, 2020 JCR, and 2021 JCR, respectively, were included in this study. The citation advantage of hybrid Gold open access articles over subscription articles in 2018 was 1.45 (95% confidence interval (CI), 1.24–1.65); in 2019, it was 1.31 (95% CI, 1.20–1.41); in 2020, it was 1.30 (95% CI, 1.20–1.39); and in 2021, it was 1.31 (95% CI, 1.20–1.42). In the ‘Clinical Medicine’ discipline, the articles published in the hybrid journal as hybrid Gold open access had a greater number of citations when compared to those published as a subscription, self-archived, or otherwise openly accessible option.

https://doi.org/10.3390/publications11020021

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"Open Access Citation Advantage? A Local Study at a Large Research University"


This study examines the open access citation advantage of gold open access (OA) journal articles published at a large U.S. research university. Most studies that examine the open access citation advantage focus on specific journals, disciplines, countries or global output. Local citation patterns may differ from these larger patterns. . . . This study reports on a method and compares average citation counts for subscription and gold OA journal articles using Web of Science. Gold OA physics journals showed a definite open access citation advantage, whereas other disciplines showed no difference or no open access citation advantage.

https://doi.org/10.1002/pra2.2017.14505401126

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"Do Altmetric Scores Reflect Article Quality? Evidence from the UK Research Excellence Framework 2021"


Altmetrics are web-based quantitative impact or attention indicators for academic articles that have been proposed to supplement citation counts. This article reports the first assessment of the extent to which mature altmetrics from Altmetric.com and Mendeley associate with individual article quality scores. It exploits expert norm-referenced peer review scores from the UK Research Excellence Framework 2021 for 67,030+ journal articles in all fields 2014–2017/2018, split into 34 broadly field-based Units of Assessment (UoAs). Altmetrics correlated more strongly with research quality than previously found, although less strongly than raw and field normalized Scopus citation counts. Surprisingly, field normalizing citation counts can reduce their strength as a quality indicator for articles in a single field. For most UoAs, Mendeley reader counts are the best altmetric (e.g., three Spearman correlations with quality scores above 0.5), tweet counts are also a moderate strength indicator in eight UoAs (Spearman correlations with quality scores above 0.3), ahead of news (eight correlations above 0.3, but generally weaker), blogs (five correlations above 0.3), and Facebook (three correlations above 0.3) citations, at least in the United Kingdom. In general, altmetrics are the strongest indicators of research quality in the health and physical sciences and weakest in the arts and humanities.

https://doi.org/10.1002/asi.24751

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"Evaluating the Ability of Open-Source Artificial Intelligence to Predict Accepting-Journal Impact Factor and Eigenfactor Score Using Academic Article Abstracts: Cross-sectional Machine Learning Analysis"


Objective:

We sought to evaluate the performance of open-source artificial intelligence to predict the impact factor or Eigenfactor score tertile using academic article abstracts.

Methods:

PubMed-indexed articles published between 2016 and 2021 were identified with the Medical Subject Headings (MeSH) terms "ophthalmology," "radiology," and "neurology." Journals, titles, abstracts, author lists, and MeSH terms were collected. Journal impact factor and Eigenfactor scores were sourced from the 2020 Clarivate Journal Citation Report. The journals included in the study were allocated percentile ranks based on impact factor and Eigenfactor scores, compared with other journals that released publications in the same year. All abstracts were preprocessed, which included the removal of the abstract structure, and combined with titles, authors, and MeSH terms as a single input. The input data underwent preprocessing with the inbuilt ktrain Bidirectional Encoder Representations from Transformers (BERT) preprocessing library before analysis with BERT. Before use for logistic regression and XGBoost models, the input data underwent punctuation removal, negation detection, stemming, and conversion into a term frequency-inverse document frequency array. Following this preprocessing, data were randomly split into training and testing data sets with a 3:1 train:test ratio. Models were developed to predict whether a given article would be published in a first, second, or third tertile journal (0-33rd centile, 34th-66th centile, or 67th-100th centile), as ranked either by impact factor or Eigenfactor score. BERT, XGBoost, and logistic regression models were developed on the training data set before evaluation on the hold-out test data set. The primary outcome was overall classification accuracy for the best-performing model in the prediction of accepting journal impact factor tertile.

Results:

There were 10,813 articles from 382 unique journals. The median impact factor and Eigenfactor score were 2.117 (IQR 1.102-2.622) and 0.00247 (IQR 0.00105-0.03), respectively. The BERT model achieved the highest impact factor tertile classification accuracy of 75.0%, followed by an accuracy of 71.6% for XGBoost and 65.4% for logistic regression. Similarly, BERT achieved the highest Eigenfactor score tertile classification accuracy of 73.6%, followed by an accuracy of 71.8% for XGBoost and 65.3% for logistic regression.

Conclusions:

Open-source artificial intelligence can predict the impact factor and Eigenfactor score of accepting peer-reviewed journals. Further studies are required to examine the effect on publication success and the time-to-publication of such recommender systems.

https://doi.org/10.2196/42789

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"Revisiting Methodology for Identifying Open Access Advantages"


This study revisited the methodology for identifying the effects of open access and revealed the causes for contradictory conclusions using four indices for journals that transitioned from subscription to open access. . . . Although the aggregated data of the eight journals indicated that open access had a positive effect, the effect varied across journals. A few journals produced different results between the two citation scores as well as between citation scores and number of citations or articles. Furthermore, a publisher’s choice of which journal to shift to open access influenced their performance after the shift.

https://doi.org/10.1007/s12109-023-09946-0

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"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"


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.

https://doi.org/10.1007/s11192-023-04653-1

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"Requiem for a Tweet — Is There a Future for the Academic Social Capital Held on the Platform?"


The mechanisms through which this network status can be exchanged into academic advantage are not straightforward, but any academic who has achieved a degree of popularity online can attest to the direct and indirect advantages which this has brought to their career.. . . What if that capital is now worthless? It’s a strange position that has the potential to leave academics clinging on to their Twitter accounts long after the beneficial impact of the platform has evaporated in a mushroom cloud of moving fast and breaking things. The collapse of Twitter would be a significant event within higher education, analogous to (though not on the same scale as) citational rankings being reset overnight.

https://cutt.ly/VMZmyaA

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Digital Preservation Coalition: "Understanding User Needs: A Case Study from the National Library of Scotland"


This case study looks at the approaches to user engagement with National Library of Scotland (NLS) maps website users, and how this informs digital preservation decisions. After a brief description of the NLS maps website structure, it examines user expectations of the NLS maps website, how these have developed over time, and the main purposes users have for visiting the website. The main research methods which have been employed to consult with users are then outlined, including user surveys, web-analytics, mystery visitor reports, and enquiries.

http://doi.org/10.7207/twgn22-01

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"Gender and Country Biases in Wikipedia Citations to Scholarly Publications"


We investigate gender- and country-based biases in Wikipedia citation practices using linked data from the Web of Science and a Wikipedia citation dataset. . . . we show that publications by women are cited less by Wikipedia than expected, and publications by women are less likely to be cited than those by men. Scholarly publications by authors affiliated with non-Anglosphere countries are also disadvantaged in getting cited by Wikipedia. . . . The level of gender- or country-based inequalities varies by research field, and the gender-country intersectional bias is prominent in math-intensive STEM fields.

https://doi.org/10.1002/asi.24723

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"Guest Post – Wikipedia’s Citations Are Influencing Scholars and Publishers"


A well-written Wikipedia page will cite scholarly publications with links to the articles in those citations that can be accessed immediately by users. At the 2019 Charleston Conference keynote, Internet Archive founder Brewster Kahle claimed that 6% of Wikipedia readers click on a link in the footnotes (although another study found that it was more like 0.03%). In 2016, Wikipedia was the 6th-largest referrer for DOIs, with half of referrals successfully authenticating to access the article. External links on Wikipedia produce an estimated 7 million dollars of revenue per month. Given that Wikipedia is such a popular website, it’s unsurprising that academic publishers are actively pursuing ways to promote their work on Wikipedia.

https://cutt.ly/tNIZJtG

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"Choices of Immediate Open Access and the Relationship to Journal Ranking and Publish-And-Read Deals"


The study asks how choices of immediate gold and hybrid open access are related to journal ranking and how the uptake of immediate open access is affected by transformative publish-and-read deals, pushed by recent science policy. Data consists of 186,621 articles published with a Norwegian affiliation in the period 2013–2021, all of which were published in journals ranked in a National specific ranking, on one of two levels according to their importance, prestige, and perceived quality within a discipline. The results are that researchers chose to have their articles published as hybrid two times as often in journals on the most prestigious level compared with journals on the normal level. The opposite effect was found with gold open access where publishing on the normal level was chosen three times more than on the high level. This can be explained by the absence of highly ranked gold open access journals in many disciplines. With the introduction of publish-and-read deals, hybrid open access has boosted and become a popular choice enabling the researcher to publish open access in legacy journals.

https://cutt.ly/oNpijrR

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