Factors Associated With Open Access Publishing Costs in Oncology Journals: Cross-sectional Observational Study

Abstract:  Background:

Open access (OA) publishing represents an exciting opportunity to facilitate the dissemination of scientific information to global audiences. However, OA publishing is often associated with significant article processing charges (APCs) for authors, which may thus serve as a barrier to publication.

Objective:In this observational cohort study, we aimed to characterize the landscape of OA publishing in oncology and, further, identify characteristics of oncology journals that are predictive of APCs.

Methods:We identified oncology journals using the SCImago Journal & Country Rank database. All journals with an OA publication option and APC data openly available were included. We searched journal websites and tabulated journal characteristics, including APC amount (in US dollars), OA model (hybrid vs full), 2-year impact factor (IF), H-index, number of citable documents, modality/treatment specific (if applicable), and continent of origin. All APCs were converted to US-dollar equivalents for final analyses. Selecting variables with significant associations in the univariable analysis, we generated a multiple regression model to identify journal characteristics independently associated with OA APC amount. An audit of a random 10% sample of the data was independently performed by 2 authors to ensure data accuracy, precision, and reproducibility.

Results:Of 367 oncology journals screened, 251 met the final inclusion criteria. The median APC was US $2957 (IQR 1958-3450). The majority of journals (n=156, 62%) adopted the hybrid OA publication model and were based in Europe (n=119, 47%) or North America (n=87, 35%). The median (IQR) APC for all journals was US $2957 (1958-3540). Twenty-five (10%) journals had APCs greater than US $4000. There were 10 (4%) journals that offered OA publication with no publication charge. Univariable testing showed that journals with a greater number of citable documents (P<.001), higher 2-year IF (P<.001), higher H-index (P<.001), and those using the hybrid OA model (P<.001), or originating in Europe or North America (P<.001) tended to have higher APCs. In our multivariable model, the number of citable documents (?=US $367, SD US $133; P=.006), 2-year IF (US $1144, SD US $177; P<.001), hybrid OA publishing model (US $991, SD US $189; P<.001), and North American origin (US $838, SD US $186; P<.001) persisted as significant predictors of processing charges.

Conclusions:OA publication costs are greater in oncology journals that publish more citable articles, use the hybrid OA model, have a higher IF, and are based in North America or Europe. These findings may inform targeted action to help the oncology community fully appreciate the benefits of open science.

Journal of Medical Internet Research – 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

Abstract:  Strategies to improve the selection of appropriate target journals may reduce delays in disseminating research results. Machine learning is increasingly used in content-based recommender algorithms to guide journal submissions for academic articles.


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


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.


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.


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.

Measuring Back: Bibliodiversity and the Journal Impact Factor brand. A Case study of IF-journals included in the 2021 Journal Citations Report. | Zenodo

Abstract:  Little attention has been devoted to whether the Impact Factor (IF) can be considered a responsible metric in light of bibliodiversity. This paper critically engages with this question in measuring the following variables of IF journals included in the 2021 Journal CItation Reports and examining their distribution: publishing models (hybrid, Open Access with or without fees, subscription), world regions, language(s) of publication, subject categories, publishers, and the prices of article processing charges (APC) if any. Our results show that the quest for prestige or perceived quality through the IF brand poses serious threats to bibliodiversity. The IF brand can indeed hardly be considered a responsible metric insofar as it perpetuates publishing concentration, maintains a domination of the Global North and its attendant artificial image of mega producer of scholarly content, does not promote linguistic diversity, and de-incentivizes fair and equitable open access by entrenching fee-based OA delivery options with rather high APCs.


Elsevier journal under fire for rejecting paper that didn’t cite enough of its old papers

“A scholarly journal run by the Dutch publishing giant Elsevier has come under scrutiny for rejecting a paper submitted for publication because, among other reasons, it didn’t cite enough of the journal’s previously published papers.

The rejection letter, from the International Journal of Hydrogen Energy (IJHE), which is published by Elsevier on behalf of the International Association for Hydrogen Energy, reads: “while the subject is within the scope of the journal, there are only four citations to past papers published in IJHE out of 150 references cited.”

The letter came to light after microbiologist-turned-scientific integrity expert Elisabeth Bik posted it on Twitter on Jan. 19….”

‘The attitude of publishers is a barrier to open access’ | UKSG

“Transitioning to open research is incredibly important for the University of Liverpool for two reasons: the external environment we are now operating in, and our own philosophy and approach to research.

But there are barriers, particularly the research culture and the attitude of publishers….

In my experience, the biggest barrier is culture: researchers are used to operating in a particular way. Changing practice and mindset takes time and must be conducted sensitively.

Open research benefits all researchers, so having their support on this journey is vitally important.

Some researchers are concerned that publishing their work open access has implications for their intellectual property (IP) rights. In fact, this is a perceived problem, since the same IP protections apply to all work, whether published behind a paywall or published open access.

Despite the recognition that citation metrics are not a suitable proxy for research assessment, some researchers continue to seek the kudos of publishing in a so-called prestige journal with a high-impact factor, such as ‘Nature’.  They see this as a key career goal and worry their progression will falter without this achievement….

So, while I acknowledge there has been significant progress towards open access globally, and in particular compliance with UKRI’s open access policy, the attitude of publishers which are driven by profit margins continues to be an unacceptable barrier….”

Market forces influence editorial decisions – ScienceDirect

“In this issue of Cortex Huber et al. recount their experience in attempting to update the scientific record through an independent replication of a published study (Huber, Potter, & Huszar, 2019). In general, publishers resist issuing retractions, refutations or corrections to their stories or papers for fear of losing public trust, diminishing their brand and possibly ceding their market share (Sullivan, 2018). Unfortunately, this is just one way that market logic – retaining a competitive advantage among peers – explicitly or implicitly influences editorial priorities and decisions more broadly….

There’s the well-known tautology that news is what newsrooms decide to cover and what’s “newsworthy” is influenced by market logic. That news organizations, charged with relating truth and facts, are subject to market-based decisions is a major source of contention among the discerning public. It should be even more contentious that the stewards of scientific knowledge, academic publishers, are also beholden to it….

Although top journals are loathe to admit they ‘chase cites’ (Editorial, 2018), market forces make this unavoidable. One example is a strategy akin to product cost cross subsidization such as when in journalism profitable traffic-driving, click-bait articles subsidize more costly and in-depth, long-form investigative reporting. In order to attract the ‘best’ science, top journals must maintain a competitive impact factor. If the impact factor strays too far from the nearest competitor, then the journal will have trouble publishing the science it deems as most important because of the worth coveted researchers place on perceived impact….

Although publishers tout the value of replications and pay lip service to other reformative practices, their policies in this regard are often vague and non-committal….

Most professional editors are committed to advancing strong science, but however well-intentioned and sought in good faith reforms are, they are necessarily hamstrung by market forces. This includes restrained requirements for more rigorous and responsible research conduct. Journals do not want to put in place policies that are seemingly so onerous that authors decide to instead publish in competing but less demanding journals. Researchers need incentives for and enforcement of more rigorous research practices, but they want easier paths to publication. The result is that new policies at top journals allow publishers to maintain a patina of progressiveness in the absence of real accountability….

The reforms suggested by Huber et al. are welcome short-term fixes, but the community should demand longer-term solutions that break up the monopoly of academic publishers and divorce the processes of evaluation, publication and curation (Eisen and Polka, 2018). Only then may we wrest the power of science’s stewardship from the heavy hand of the market.”

Thoughts on the Many Different Paths to Achieving Open Access: Keynote with Dr. Ross Mounce – Library Events Calendar – LJMU Library

“Professor George Talbot, Pro-Vice Chancellor (Research) and Dean of Arts and Sciences, Edge Hill University will begin Open Research Week 2023 and welcome our keynote speaker, Dr. Ross Mounce. 

In this talk, Ross will reflect on how progress towards providing open access to all academic research is going; the good, the bad, and the ugly. 

The good is: we’re starting to realise that a lot of the problem boils down to copyright issues. The emergence and normalisation of rights retention is undoubtedly healthy.?The bad news is: there are significant problems in the way that money is being spent to enable open access e.g. “transformative agreements” (sic). Transformative for whom??The ugly: Journal Impact Factor™?is statistically illiterate, negotiable, and irreproducible, but some researchers are still making decisions using it.? ?The real question now is not can we get universal open access to research, but how.”

The Great Inflation: How COVID-19 affected the Journal Impact Factor of high impact medical journals

Abstract:  The journal impact factor (IF) is the leading method of scholarly assessment in today’s research world, influencing where scholars submit their research and funders distribute their resources. The Coronavirus disease 2019 (COVID-19), one of the most serious health crises, resulted in an unprecedented surge of publications across all areas of knowledge. An important question is whether COVID-19 affected the “gold standard of scholarly assessment”. We took as an example six high impact general medicine journals (Annals, BMJ, Lancet, Nature, NEJM and JAMA) and searched the literature using the Web of Science database for manuscripts published between January 1, 2019 and December 31, 2021. To assess the effect of COVID-19 and non-COVID-19 literature in their scholarly impact, we calculated their annual IFs and percentage changes. Thereafter, we estimated the citation probability of COVID-19 and non-COVID-19 publications along with their publication and citation rates by journal. A significant increase in IF change for COVID-19 manuscripts published from 2019 to 2020 was seen, against non-COVID-19 ones. The likelihood of highly cited publications was significantly increased in COVID-19 manuscripts from 2019 to 2021.The publication and citation rates of COVID-19 publications followed a positive trajectory, as opposed to non-COVID-19. The citation rate for COVID-19 publications peaked 10 months earlier than the publication rate. The rapid surge of COVID-19 publications emphasised the capacity of scientific communities to respond against a global health emergency, yet inflated IFs create ambiguity as benchmark tools for assessing scholarly impact. The immediate implication is a loss in value of and trust on journal IFs as metrics of research and scientific rigour perceived by academia and the society. Loss of confidence towards procedures employed by highly reputable publishers may incentivise authors to exploit the publication process by monopolising their research on COVID-19 and encourage them towards publishing in journals of predatory behaviour.


‘Stop Congratulating Colleagues for Publishing in High-Impact Factor Journals’ – The Wire Science

The current scholarly publishing system is detrimental to the pursuit of knowledge and needs a radical shift. Publishers have already anticipated new trends and have tried to protect their profits.
Current publishers’ power stems from the historical roots of their journals – and researchers are looking for symbolic status in the eye of their peers by publishing in renowned journals.
To counter them effectively, we need to identify obstacles that researchers themselves might face. Journals still perform some useful tasks and it requires effort to devise working alternatives.
There have already been many attempts and partial successes to drive a new shift in scholarly publishing. Many of them should be further developed and generalised.
In this excerpt from a report prepared by the Basic Research Community for Physics, the authors discuss these successes and make recommendations to different actors….”

Impact Factors, Altmetrics, and Prestige, Oh My: The Relationship Between Perceived Prestige and Objective Measures of Journal Quality | SpringerLink

Abstract:  The focus of this work is to examine the relationship between subjective and objective measures of prestige of journals in our field. Findings indicate that items pulled from Clarivate, Elsevier, and Google all have statistically significant elements related to perceived journal prestige. Just as several widely used bibliometric metrics related to prestige, so were altmetric scores.


Open Access and Research Metrics – ChronosHub

“Let’s talk about research metrics, notably journal and article metrics, in an open access context. Is open access content read and hence cited more widely? Do open access journals have a higher impact factor than non-OA journals, or vice versa? And how does flipping a journal from closed to open affect the Impact Factor? Should we be looking at other metrics for open access content? And what are authors looking for, when choosing journals to submit their articles to? Our panelists will share their insights and possible answers to these questions through short presentations and a discussion.”

“Superior identification index – Quantifying the capability of academic journals to recognize good research

Abstract:  In this paper we present “superior identification index” (SII), a metric to quantify the capability of academic journals to recognize top papers restricted by specific time window and study field. Intuitively, SII is the percentage of papers from a journal in the top p% papers in the field. SII provides flexible framework to make trade-offs on journal quality and quantity, as p rises it puts more weight on quantity and less weight on quality. Concerns on the p selection are discussed, and extended metrics of SII, including superior identification efficiency (SIE) and paper rank percentile (PRP), were proposed to sketch other dimensions of journal performance. Based on bibliometric data from ecological field, we find that as p increases, the correlation between SIE and JIF first rises then drops, indicating that JIF might most likely reflect “how well a journal identifies the top 26~34% papers in the field”. Hopefully, the new proposed SII metric and its extensions could promote the quality awareness and provide flexible tools for research evaluation.

Starstruck by journal prestige and citation counts? On students’ bias and perceptions of trustworthiness according to clues in publication references | SpringerLink

Abstract:  Research is becoming increasingly accessible to the public via open access publications, researchers’ social media postings, outreach activities, and popular disseminations. A healthy research discourse is typified by debates, disagreements, and diverging views. Consequently, readers may rely on the information available, such as publication reference attributes and bibliometric markers, to resolve conflicts. Yet, critical voices have warned about the uncritical and one-sided use of such information to assess research. In this study we wanted to get insight into how individuals without research training place trust in research based on clues present in publication references. A questionnaire was designed to probe respondents’ perceptions of six publication attributes. A total of 148 students responded to the questionnaire of which 118 were undergraduate students (with limited experience and knowledge of research) and 27 were graduate students (with some knowledge and experience of research). The results showed that the respondents were mostly influenced by the number of citations and the recency of publication, while author names, publication type, and publication origin were less influential. There were few differences between undergraduate and graduate students, with the exception that undergraduate students more strongly favoured publications with multiple authors over publications with single authors. We discuss possible implications for teachers that incorporate research articles in their curriculum.


The impact factors of social media users’ forwarding behavior of COVID-19 vaccine topic: Based on empirical analysis of Chinese Weibo users – PMC

Abstract:  Introduction

Social media, an essential source of public access to information regarding the COVID-19 vaccines, has a significant effect on the transmission of information regarding the COVID-19 vaccines and helps the public gain correct insights into the effectiveness and safety of the COVID-19 vaccines. The forwarding behavior of social media users on posts concerned with COVID-19 vaccine topics can rapidly disseminate vaccine information in a short period, which has a significant effect on transmission and helps the public access relevant information. However, the factors of social media users’ forwarding posts are still uncertain thus far. In this paper, we investigated the factors of the forwarding COVID-19 vaccines Weibo posts on Chinese social media and verified the correlation between social network characteristics, Weibo textual sentiment characteristics, and post forwarding.


This paper used data mining, machine learning, sentiment analysis, social network analysis, and regression analysis. Using “???? (COVID-19 vaccine)” as the keyword, we used data mining to crawl 121,834 Weibo posts on Sina Weibo from 1 January 2021 to 31 May 2021. Weibo posts not closely correlated with the topic of the COVID-19 vaccines were filtered out using machine learning. In the end, 3,158 posts were used for data analysis. The proportions of positive sentiment and negative sentiment in the textual of Weibo posts were calculated through sentiment analysis. On that basis, the sentiment characteristics of Weibo posts were determined. The social network characteristics of information transmission on the COVID-19 vaccine topic were determined through social network analysis. The correlation between social network characteristics, sentiment characteristics of the text, and the forwarding volume of posts was verified through regression analysis.


The results suggest that there was a significant positive correlation between the degree of posting users in the social network structure and the amount of forwarding. The relationship between the closeness centrality and the forwarding volume was significantly positive. The betweenness centrality was significantly positively correlated with the forwarding volume. There was no significant relationship between the number of posts containing more positive sentiments and the forwarding volume of posts. There was a significant positive correlation between the number of Weibo posts containing more negative sentiments and the forwarding volume.


According to the characteristics of users, COVID-19 vaccine posts from opinion leaders, “gatekeepers,” and users with high-closeness centrality are more likely to be reposted. Users with these characteristics should be valued for their important role in disseminating information about COVID-19 vaccines. In addition, the sentiment contained in the Weibo post is an important factor influencing the public to forward vaccine posts. Special attention should be paid to the negative sentimental tendency contained in this post on Weibo to mitigate the negative impact of the information epidemic and improve the transmission effect of COVID-19 vaccine information.