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Pablo Dorta-González

Publications and source records attributed to Pablo Dorta-González.

At least 19 recordsLinked to original sources

Citation of scientific evidence from video description and its association with attention and impact

This study investigates how YouTube content creators utilize scientific evidence in videos. Log-linear regression examines the influence of alternative communication channels on video creators in Biotechnology, using data from 81,302 papers (2018-2023). This reveals a positive association with news articles and Wikipedia pages, but a negative association with scientific papers, policy documents, and patents. Despite the potential for enriching discussions, science video creators seem to favor materials with wider public attention over influential science, technology, and policy papers. These findings suggest a need for improved dissemination strategies for scientific research. Authors, universities, and journals should consider how their work can be made more accessible and engaging for science communicators on video.

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A two-stage model for factors influencing citation counts

This work aims to study a count response random variable, the number of citations of a research paper, affected by some explanatory variables through a suitable regression model. Due to the fact that the count variable exhibits substantial variation since the sample variance is larger than the sample mean, the classical Poisson regression model seems not to be appropriate. We concentrate attention on the negative binomial regression model, which allows the variance of each measurement to be a function of its predicted value. Nevertheless, the process of citations of papers may be divided into two parts. In the first stage, the paper has no citations, and the second part provides the intensity of the citations. A hurdle model for separating the documents with citations and those without citations is considered. The dataset for the empirical application consisted of 43,190 research papers in the field of Economics and Business from 2014-2021, obtained from The Lens database. Citation counts and social attention scores for each article were gathered from Altmetric database. The main findings indicate that both collaboration and funding have a positive impact on citation counts and reduce the likelihood of receiving zero citations. Higher journal impact factors lead to higher citation counts, while lower peer review ratings lead to fewer citations and a higher probability of zero citations. Mentions in news, blogs, and social media have varying but generally limited effects on citation counts. Open access via repositories (green OA) correlates with higher citation counts and a lower probability of zero citations. In contrast, OA via the publisher's website without an explicit open license (bronze OA) is associated with higher citation counts but also with a higher probability of zero citations.

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Which kind of research papers influence policymaking

This study examines the use of evidence in policymaking by analysing a range of journal and article attributes, as well as online engagement metrics. It employs a large-scale citation analysis of nearly 150,000 articles covering diverse policy topics. The findings highlight that scholarly citations exert the strongest positive influence on policy citations. Articles from journals with a higher citation impact and larger Mendeley readership are cited more frequently in policy documents. Other online engagements, such as news and blog mentions, also boost policy citations, while mentions on social media X have a negative effect. The finding that highly cited and widely read papers are also frequently referenced in policy documents likely reflects the perception among policymakers that such research is more trustworthy. In contrast, papers that derive their influence primarily from social media tend to be cited less often in policy contexts.

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Effect of perceived preprint effectiveness and research intensity on posting behaviour

Open science is increasingly recognised worldwide, with preprint posting emerging as a key strategy. This study explores the factors influencing researchers' adoption of preprint publication, particularly the perceived effectiveness of this practice and research intensity indicators such as publication and review frequency. Using open data from a comprehensive survey with 5,873 valid responses, we conducted regression analyses to control for demographic variables. Researchers' productivity, particularly the number of journal articles and books published, greatly influences the frequency of preprint deposits. The perception of the effectiveness of preprints follows this. Preprints are viewed positively in terms of early access to new research, but negatively in terms of early feedback. Demographic variables, such as gender and the type of organisation conducting the research, do not have a significant impact on the production of preprints when other factors are controlled for. However, the researcher's discipline, years of experience and geographical region generally have a moderate effect on the production of preprints. These findings highlight the motivations and barriers associated with preprint publication and provide insights into how researchers perceive the benefits and challenges of this practice within the broader context of open science.

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Linking Science and Industry: Influence of Scientific Research on Technological Innovation through Patent Citations

This study explores the connection between patent citations and scientific publications across six fields: Biochemistry, Genetics, Pharmacology, Engineering, Mathematics, and Physics. Analysing 117,590 papers from 2014 to 2023, the research emphasises how publication year, open access (OA) status, and discipline influence patent citations. Openly accessible papers, particularly those in hybrid OA journals or green OA repositories, are significantly more likely to be cited in patents, seven times more than those mentioned in blogs, and over twice as likely compared to older publications. However, papers with policy-related references are less frequently cited, indicating that patents may prioritise commercially viable innovations over those addressing societal challenges. Disciplinary differences reveal distinct innovation patterns across sectors. While academic visibility via blogs or platforms like Mendeley increases within scholarly circles, these have limited impact on patent citations. The study also finds that increased funding, possibly tied to applied research trends and fully open access journals, negatively affects patent citations. Social media presence and the number of authors have minimal impact. These findings highlight the complex factors shaping the integration of scientific research into technological innovations.

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Generative artificial intelligence usage by researchers at work: Effects of gender, career stage, type of workplace, and perceived barriers

The integration of generative artificial intelligence technology into research environments has become increasingly common in recent years, representing a significant shift in the way researchers approach their work. This paper seeks to explore the factors underlying the frequency of use of generative AI amongst researchers in their professional environments. As survey data may be influenced by a bias towards scientists interested in AI, potentially skewing the results towards the perspectives of these researchers, this study uses a regression model to isolate the impact of specific factors such as gender, career stage, type of workplace, and perceived barriers to using AI technology on the frequency of use of generative AI. It also controls for other relevant variables such as direct involvement in AI research or development, collaboration with AI companies, geographic location, and scientific discipline. Our results show that researchers who face barriers to AI adoption experience an 11% increase in tool use, while those who cite insufficient training resources experience an 8% decrease. Female researchers experience a 7% decrease in AI tool usage compared to men, while advanced career researchers experience a significant 19% decrease. Researchers associated with government advisory groups are 45% more likely to use AI tools frequently than those in government roles. Researchers in for-profit companies show an increase of 19%, while those in medical research institutions and hospitals show an increase of 16% and 15%, respectively. This paper contributes to a deeper understanding of the mechanisms driving the use of generative AI tools amongst researchers, with valuable implications for both academia and industry.

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Societal and scientific impact of policy research: A large-scale empirical study of some explanatory factors using Altmetric and Overton

This study investigates how scientific research influences policymaking by analyzing citations of research articles in policy documents (policy impact) for nearly 125,000 articles across 434 public policy journals. We reveal distinct citation patterns between policymakers and other stakeholders like researchers, journalists, and the public. News and blog mentions, social media engagement, and open access publications (excluding fully open access) significantly increase the likelihood of a research article being cited in policy documents. Conversely, articles locked behind paywalls and those published under the full open access model (based on Altmetric data) have a lower chance of being policy-cited. Publication year and policy type show no significant influence. Our findings emphasize the crucial role of science communication channels like news media and social media in bridging the gap between research and policy. Interestingly, academic citations hold a weaker influence on policy citations compared to news mentions, suggesting a potential disconnect between how researchers reference research and how policymakers utilize it. This highlights the need for improved communication strategies to ensure research informs policy decisions more effectively. This study provides valuable insights for researchers, policymakers, and science communicators. Researchers can tailor their dissemination efforts to reach policymakers through media channels. Policymakers can leverage these findings to identify research with higher policy relevance. Science communicators can play a critical role in translating research for policymakers and fostering dialogue between the scientific and policymaking communities.

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A field- and time-normalized Bayesian approach to measuring the impact of a publication

Measuring the impact of a publication in a fair way is a significant challenge in bibliometrics, as it must not introduce biases between fields and should enable comparison of the impact of publications from different years. In this paper, we propose a Bayesian approach to tackle this problem, motivated by empirical data demonstrating heterogeneity in citation distributions. The approach uses the a priori distribution of citations in each field to estimate the expected a posteriori distribution in that field. This distribution is then employed to normalize the citations received by a publication in that field. Our main contribution is the Bayesian Impact Score, a measure of the impact of a publication. This score is increasing and concave with the number of citations received and decreasing and convex with the age of the publication. This means that the marginal score of an additional citation decreases as the cumulative number of citations increases and increases as the time since publication of the document grows. Finally, we present an empirical application of our approach in eight subject categories using the Scopus database and a comparison with the normalized impact indicator Field Citation Ratio from the Dimensions AI database.

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Modeling citation concentration through a mixture of Leimkuhler curves

When a graphical representation of the cumulative percentage of total citations to articles, ordered from most cited to least cited, is plotted against the cumulative percentage of articles, we obtain a Leimkuhler curve. In this study, we noticed that standard Leimkuhler functions may not be sufficient to provide accurate fits to various empirical informetrics data. Therefore, we introduce a new approach to Leimkuhler curves by fitting a known probability density function to the initial Leimkuhler curve, taking into account the presence of a heterogeneity factor. As a significant contribution to the existing literature, we introduce a pair of mixture distributions (called PG and PIG) to bibliometrics. In addition, we present closed-form expressions for Leimkuhler curves. {Some measures of citation concentration are examined empirically for the basic models (based on the Power {and Pareto distributions}) and the mixed models derived from {these}.} An application to two sources of informetric data was conducted to see how the mixing models outperform the standard basic models. The different models were fitted using non-linear least squares estimation.

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Does society show differential attention to researchers based on gender and field?

While not all researchers prioritize social impact, it is undeniably a crucial aspect that adds significance to their work. The objective of this paper is to explore potential gender differences in the social attention paid to researchers and to examine their association with specific fields of study. To achieve this goal, the paper analyzes four dimensions of social influence and examines three measures of social attention to researchers. The dimensions are media influence (mentions in mainstream news), political influence (mentions in public policy reports), social media influence (mentions in Twitter), and educational influence (mentions in Wikipedia). The measures of social attention to researchers are: proportion of publications with social mentions (social attention orientation), mentions per publication (level of social attention), and mentions per mentioned publication (intensity of social attention). By analyzing the rankings of authors -- for the four dimensions with the three measures in the 22 research fields of the Web of Science database -- and by using Spearman correlation coefficients, we conclude that: 1) significant differences are observed between fields; 2) the dimensions capture different and independent aspects of the social impact. Finally, we use non-parametric means comparison tests to detect gender bias in social attention. We conclude that for most fields and dimensions with enough non-zero altmetrics data, gender differences in social attention are not predominant, but are still present and vary across fields.

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The funding effect on citation and social attention: the UN Sustainable Development Goals (SDGs) as a case study

Purpose: Academic citation and social attention measure different dimensions in the impact of research results. We quantify the contribution of funding to both indicators considering the differences attributable to the research field and access type. Design/methodology/approach: Citation and social attention accumulated until the year 2021 of more than 367 thousand research articles published in the year 2018, are studied. We consider funding acknowledgements in the research articles. The data source is Dimensions and the units of study are research articles in the UN Sustainable Development Goals. Findings: Most cited goals by researchers do not coincide with those that arouse greater social attention. A small proportion of articles accumulates a large part of the citations and most of the social attention. Both citation and social attention grow with funding. Thus, funded research has a greater probability of being cited in academic articles and mentioned in social media. Funded research receives on average two to three times more citations and 2.5 to 4.5 times more social attention than unfunded research. Moreover, the open access modalities gold and hybrid have the greatest advantages in citation and social attention due to funding. Originality: The joint evaluation of the effect of both funding and open access on social attention. Research limitations: Specific topics were studied in a specific period. Studying other topics and/or different time periods might result in different findings. Practical implications: When funding to publish in open or hybrid access journals is not available, it is advisable to self-archiving the pre-print or post-print version in a freely accessible repository. Social implications: Although cautiously, it is also advisable to consider the social impact of the research to complement the scientific impact in the evaluation of the research.

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A Multiple Linear Regression Analysis to Measure the Journal Contribution to the Social Attention of Research

This paper proposes a three-year average of social attention as a more reliable measure of social impact for journals, since the social attention of research can vary widely among scientific articles, even within the same journal. The proposed measure is used to evaluate a journal's contribution to social attention in comparison to other bibliometric indicators. The study uses Dimensions as a data source and examines research articles from 76 disciplinary library and information science journals through multiple linear regression analysis. The study identifies socially influential journals whose contribution to social attention is twice that of scholarly impact as measured by citations. In addition, the study finds that the number of authors and open access have a moderate impact on social attention, while the journal impact factor has a negative impact and funding has a small impact.

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Influencing factors of Twitter mentions of scientific papers

Purpose: This paper explores some influencing factors of Twitter mentions of scientific research. The results can help to understand the relationships between various altmetrics. Design/methodology/approach: Data on research mentions in Altmetric and a multiple linear regression analysis are used. Findings: Among the variables analyzed, the number of mainstream news is the factor that most influences the number of mentions on Twitter, followed by the fact of dealing with a highly topical issue such as COVID-19. The influence is weaker in the case of expert recommendations and the consolidation of knowledge in the form of a review. The lowest influence corresponds to both the public policies through references in reports, and to citations in Wikipedia, while mentions in patent applications does not have a significant influence. Research limitations: A specific field was studied in a specific time frame. Studying other fields and/or different time periods might result in different findings. Practical implications: Governments increasingly push researchers toward activities with societal impact and this study can help understand how different factors affect social media attention. Originality/value: Understanding social media attention of research is essential when implementing societal impact indicators.

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Collaboration Effect by Co-Authorship on Academic Citation and Social Attention of Research

Academic citation and social attention measure different dimensions of the impact of research results. Both measures do not correlate with each other, and they are influenced by many factors. Among these factors are the field of research, the type of access, and co-authorship. In this study, the increase in the impact due to co-authorship in scientific articles disaggregated by field of research and access type, was quantified. For this, the citations and social attention accumulated until the year 2021 by a total of 244,880 research articles published in the year 2018, were analyzed. The data source was Dimensions.ai, and the units of study were research articles in Economics, History and Archaeology, and Mathematics. As the main results, a small proportion of the articles received a large part of the citations and most of the social attention. Both citations and social attention in-creased, in general, with the number of co-authors. Thus, the greater the number of co-authors, the greater the probability of being cited in academic articles and mentioned on social media. The advantage in citation and social attention due to collaboration is independent of the access type for the publication. Furthermore, although collaboration with an additional co-author is in general positive in terms of citation and social attention, these positive effects reduce as the number of co-authors increases.

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Modeling the obsolescence of research literature in disciplinary journals through the age of their cited references

There are different citation habits in the research fields that influence the obsolescence of the research literature. We analyze the distinctive obsolescence of research literature in disciplinary journals in eight scientific subfields based on cited references distribution, as a synchronous approach. We use both Negative Binomial (NB) and Poisson distributions to capture this obsolescence. The corpus being examined is published in 2019 and covers 22,559 papers citing 872,442 references. Moreover, three measures to analyze the tail of the distribution are proposed: (i) cited reference survival rate, (ii) cited reference mortality rate, and (iii) cited reference percentile. These measures are interesting because the tail of the distribution collects the behavior of the citations at the time when the document starts to get obsolete in the sense that it is little cited (used). As main conclusion, the differences observed in obsolescence are so important even between disciplinary journals in the same subfield, that it would be necessary to use some measure for the tail of the citation distribution, such as those proposed in this paper, when analyzing in an appropriate way the long time impact of a journal.

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The influence of funding on the Open Access citation advantage

Some of the citation advantage in open access is likely due to more access allows more people to read and hence cite articles they otherwise would not. However, causation is difficult to establish and there are many possible bias. Several factors can affect the observed differences in citation rates. Funder mandates can be one of them. Funders are likely to have OA requirement, and well-funded studies are more likely to receive more citations than poorly funded studies. In this paper this hypothesis is tested. Thus, we studied the effect of funding on the publication modality and the citations received in more than 128 thousand research articles, of which 31% were funded. These research articles come from 40 randomly selected subject categories in the year 2016, and the citations received from the period 2016-2020 in the Scopus database. We found open articles published in hybrid journals were considerably more cited than those in open access journals. Thus, articles under the hybrid gold modality are cite on average twice as those in the gold modality. This is the case regardless of funding, so this evidence is strong. Moreover, within the same publication modality, we found that funded articles generally obtain 50% more citations than unfunded ones. The most cited modality is the hybrid gold and the least cited is the gold, well below even the paywalled. Furthermore, the use of open access repositories considerably increases the citations received, especially for those articles without funding. Thus, the articles in open access repositories (green) are 50% more cited than the paywalled ones. This evidence is remarkable and does not depend on funding. Excluding the gold modality, there is a citation advantage in more than 75% of the cases and it is considerably greater among unfunded articles. This result is strong both across fields and over time.

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Contribution of the Open Access modality to the impact of hybrid journals controlling by field and time effects

Researchers are more likely to read and cite papers to which they have access than those that they cannot obtain. Thus, the objective of this work is to analyze the contribution of the Open Access (OA) modality to the impact of hybrid journals. For this, the research articles in the year 2017 from 200 hybrid journals in four subject areas, and the citations received by such articles in the period 2017-2020 in the Scopus database, were analyzed. The journals were randomly selected from those with share of OA papers higher than some minimal value. More than 60 thousand research articles were analyzed in the sample, of which 24% under the OA modality. As results, we obtain that cites per article in both hybrid modalities strongly correlate. However, there is no correlation between the OA prevalence and cites per article in any of the hybrid modalities. There is OA citation advantage in 80% of hybrid journals. Moreover, the OA citation advantage is consistent across fields and held in time. We obtain an OA citation advantage of 50% in average, and higher than 37% in half of the hybrid journals. Finally, the OA citation advantage is higher in Humanities than in Science and Social Science.

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Employment in Tourism Industries: Are there Subsectors with a Potentially Higher Level of Income?

This work analyzes the tourist sector, the employment generated by the tourism industries, and its relationship with tourism receipts. The hypothesis is that there are tourist subsectors with a potentially higher level of income. The article studies the impact of the distribution of the employed population in the different subsectors of the tourism industry, controlling for the most important economic variables, on the level of income per arrival in 24 OECD countries, using panel data for the period 2008 to 2018. As its main result, the model indicates that the labor force that increases most the receipts per arrival is the 'travel agencies and other reservation services', followed by the 'sports and recreation industry' labor force, while having a large labor force in the 'food and beverage' or 'cultural industry' operates in the opposite direction.

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