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Enrique Orduña-Malea

Publications and source records attributed to Enrique Orduña-Malea.

14 recordsLinked to original sources

Unraveling the Ai2 Asta Scholarly Research Assistant Citation System

Despite the growing integration of Deep Research tools into academic workflows, empirical evidence on the operation, stability, and potential biases of their citation systems remains scarce. This study addresses this gap by evaluating the intensity, consistency, and bibliographic characteristics of references cited in the literature reports generated by Ai2 Asta, with the aim of understanding how its citation system operates and assessing its implications for scholarly communication. To this end, ten domain-specific queries were submitted to Asta's Summarise Literature feature, and two independent rounds of data collection were conducted. From each report, in-text citations, cited references, as well as other metrics related to the response process were extracted and examined. The results reveal high citation intensity, with reports integrating numerous in-text citations grounded in retrieved evidence and a diverse yet concentrated set of venues. However, notable instability is observed in the composition of cited references across identical queries, alongside a lack of concordance between retrieved documents and those ultimately cited, suggesting additional opaque selection mechanisms during report generation. These findings indicate that, while Ai2 Asta produces well-structured and quality reports, its instability and opacity in the citation process pose challenges in quantitative science studies due to their lack of reproducibility and transparency. Despite the restricted number of queries and disciplinary scope, the results offer valuable insights for researchers, bibliometricians, developers, and research evaluators seeking to understand, use or regulate AI-based scholarly assistants responsibly.

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Fake scientific journals are here to stay

Scientific publishing is facing an alarming proliferation of fraudulent practices that threaten the integrity of research communication. The production and dissemination of fake research have become a profitable business, undermining trust in scientific journals and distorting the evaluation processes that depend on them. This brief piece examines the problem of fake journals through a three-level typology. The first level concerns predatory journals, which prioritise financial gain over scholarly quality by charging authors publication fees while providing superficial or fabricated peer review. The second level analyses hijacked journals, in which counterfeit websites impersonate legitimate titles to deceive authors into submitting and paying for publication. The third level addresses hacked journals, where legitimate platforms are compromised through cyberattacks or internal manipulation, enabling the distortion of review and publication processes. Together, these forms of misconduct expose deep vulnerabilities in the scientific communication ecosystem, exacerbated by the pressure to publish and the marketisation of research outputs. The manuscript concludes that combating these practices requires structural reforms in scientific evaluation and governance. Only by reducing the incentives that sustain the business of fraudulent publishing can the scholarly community restore credibility and ensure that scientific communication fulfils the essential purpose of reliable advancement of knowledge.

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Research on Research Visibility

This editorial explores the significance of research visibility within the evolving landscape of academic communication, mainly focusing on the role of search engines as online meta-markets shaping the impact of research. With the rapid expansion of scientific output and the increasing reliance on algorithm-driven platforms such as Google and Google Scholar, the online visibility of scholarly work has become an essential factor in determining its reach and influence. The need for more rigorous research into academic search engine optimization (A-SEO), a field still in its infancy despite its growing relevance, is also discussed, highlighting key challenges in the field, including the lack of robust research methodologies, the skepticism within the academic community regarding the commercialization of science, and the need for standardization in reporting and measurement techniques. This editorial thus invites a multidisciplinary dialogue on the future of research visibility, with significant implications for academic publishing, science communication, research evaluation, and the global scientific ecosystem.

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2016 Google Scholar Metrics released: a matter of languages... and something else

The 2016 edition of Google Scholar Metrics was released on July 15th 2016. There haven't been any structural changes respect to previous versions, which means that most of its limitations still persist. The biggest changes are the addition of five new language rankings (Russian, Korean, Polish, Ukrainian, and Indonesian) and elimination of two other language rankings (Italian and Dutch). In addition, for reasons still unknown, this new edition doesn't include as many working paper and discussion paper series as previous editions.

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Proceedings Scholar Metrics: H Index of proceedings on Computer Science, Electrical & Electronic Engineering, and Communications according to Google Scholar Metrics (2010-2014)

The objective of this report is to present a list of proceedings (conferences, workshops, symposia, meetings) in the areas of Computer Science, Electrical & Electronic Engineering, and Communications covered by Google Scholar Metrics and ranked according to their h-index. Google Scholar Metrics only displays publications that have published at least 100 papers and have received at least one citation in the last five years (2010-2014). The searches were conducted between the 8th and 10th of December, 2015. A total of 1501 proceedings have been identified

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Does Google Scholar contain all highly cited documents (1950-2013)?

The study of highly cited documents on Google Scholar (GS) has never been addressed to date in a comprehensive manner. The objective of this work is to identify the set of highly cited documents in Google Scholar and define their core characteristics: their languages, their file format, or how many of them can be accessed free of charge. We will also try to answer some additional questions that hopefully shed some light about the use of GS as a tool for assessing scientific impact through citations. The decalogue of research questions is shown below: 1. Which are the most cited documents in GS? 2. Which are the most cited document types in GS? 3. What languages are the most cited documents written in GS? 4. How many highly cited documents are freely accessible? 4.1 What file types are the most commonly used to store these highly cited documents? 4.2 Which are the main providers of these documents? 5. How many of the highly cited documents indexed by GS are also indexed by WoS? 6. Is there a correlation between the number of citations that these highly cited documents have received in GS and the number of citations they have received in WoS? 7. How many versions of these highly cited documents has GS detected? 8. Is there a correlation between the number of versions GS has detected for these documents, and the number citations they have received? 9. Is there a correlation between the number of versions GS has detected for these documents, and their position in the search engine result pages? 10. Is there some relation between the positions these documents occupy in the search engine result pages, and the number of citations they have received?

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Reviving the past: the growth of citations to old documents

In this Digest we review a recent study released by the Google Scholar team on the apparently increasing fraction of citations to old articles from studies published in the last 24 years (1990-2013). First, we describe the main findings of their article. Secondly, we conduct an analogue study, using a different data source as well as different measures which throw very similar results, thus confirming the phenomenon. Lastly, we discuss the possible causes of this phenomenon.

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About the size of Google Scholar: playing the numbers

The emergence of academic search engines (Google Scholar and Microsoft Academic Search essentially) has revived and increased the interest in the size of the academic web, since their aspiration is to index the entirety of current academic knowledge. The search engine functionality and human search patterns lead us to believe, sometimes, that what you see in the search engine's results page is all that really exists. And, even when this is not true, we wonder which information is missing and why. The main objective of this working paper is to calculate the size of Google Scholar at present (May 2014). To do this, we present, apply and discuss up to 4 empirical methods: Khabsa & Giles's method, an estimate based on empirical data, and estimates based on direct queries and absurd queries. The results, despite providing disparate values, place the estimated size of Google Scholar in about 160 million documents. However, the fact that all methods show great inconsistencies, limitations and uncertainties, makes us wonder why Google does not simply provide this information to the scientific community if the company really knows this figure.

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Google Scholar Metrics 2014: a low cost bibliometric tool

We analyse the main features of the third edition of Google Scholar Metrics (GSM), released in June 2014, focusing on its more important changes, strengths, and weaknesses. Additionally, we present some figures that outline the dimensions of this new edition, and we compare them to those of previous editions. Principal among these figures are the number of visualized publications, publication types, languages, and the maximum and minimum h5-index and h5-median values by language, subject area, and subcategory. This new edition is marked by continuity. There is nothing new other than the updating of the time frame (2009-2013) and the removal of some redundant subcategories (from 268 to 261) for English written publications. Google has just updated the data, which means that some of the errors discussed in previous studies still persist. To sum up, GSM is a minimalist information product with few features, closed (it cannot be customized by the user), and simple (navigating it only takes a few clicks). For these reasons, we consider it a 'low cost' bibliometric tool, and propose a list of features it should incorporate in order to stop being labeled as such. Notwithstanding the above, this product presents a stability in its bibliometric indicators that supports its ability to measure and track the impact of scientific publications.

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The dark side of Open Access in Google and Google Scholar: the case of Latin-American repositories

Since repositories are a key tool in making scholarly knowledge open access, determining their presence and impact on the Web is essential, particularly in Google (search engine par excellence) and Google Scholar (a tool increasingly used by researchers to search for academic information). The few studies conducted so far have been limited to very specific geographic areas (USA), which makes it necessary to find out what is happening in other regions that are not part of mainstream academia, and where repositories play a decisive role in the visibility of scholarly production. The main objective of this study is to ascertain the presence and visibility of Latin American repositories in Google and Google Scholar through the application of page count and visibility indicators. For a sample of 137 repositories, the results indicate that the indexing ratio is low in Google, and virtually nonexistent in Google Scholar; they also indicate a complete lack of correspondence between the repository records and the data produced by these two search tools. These results are mainly attributable to limitations arising from the use of description schemas that are incompatible with Google Scholar (repository design) and the reliability of web indicators (search engines). We conclude that neither Google nor Google Scholar accurately represent the actual size of open access content published by Latin American repositories; this may indicate a non-indexed, hidden side to open access, which could be limiting the dissemination and consumption of open access scholarly literature.

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Aggregation of the web performance of internal university units as a method of quantitative analysis of a university system: the case of Spain

The aggregation of web performance (page count and visibility) of internal university units could constitute a more precise indicator than the overall web performance of the universities and, therefore, be of use in the design of university web rankings. In order to test this hypothesis, a longitudinal analysis of the internal units of the Spanish university system was conducted over the course of 2010. For the 13800 URLs identified, page count and visibility was calculated using the Yahoo API. The internal values obtained were aggregated by university and compared with the values obtained from the analysis of the university general URLs. The results indicate that, although the correlations between general and internal values are high, internal performance is low in comparison to general performance, and that they give rise to different performance rankings. The conclusion is that the aggregation of unit performance is of limited use due to the low levels of internal development of the websites, and so its use is not recommended for the design of rankings. Despite this, the internal analysis enabled the detection of, amongst other things, a low correlation between page count and visibility due to the widespread use of subdirectories and problems accessing certain content.

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Proposal for a multilevel university cybermetric analysis model

University online seats have gradually become complex systems of dynamic information where all their institutions and services are linked and potentially accessible. These online seats now constitute a central node around which universities construct and document their main activities and services. This information can be quantitative measured by cybermetric techniques in order to design university web rankings, taking the university as a global reference unit. However, previous research into web subunits shows that it is possible to carry out systemic web analyses, which open up the possibility of carrying out studies which address university diversity, necessary for both describing the university in greater detail and for establishing comparable ranking units. To address this issue, a multilevel university cybermetric analysis model is proposed, based on parts (core and satellite), levels (institutional and external) and sublevels (contour and internal), providing a deeper analysis of institutions. Finally the model is integrated into another which is independent of the technique used, and applied by analysing Harvard University as an example of use.

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U.S. academic libraries: understanding their web presence and their relationship with economic indicators

The main goal of this research is to analyze the web structure and performance of units and services belonging to U.S. academic libraries in order to check their suitability for webometric studies. Our objectives include studying their possible correlation with economic data and assessing their use for complementary evaluation purposes. We conducted a survey of library homepages, institutional repositories, digital collections, and online catalogs (a total of 374 URLs) belonging to the 100 U.S. universities with the highest total expenditures in academic libraries according to data provided by the National Center for Education Statistics (NCES). Several data points were taken and analyzed, including web variables (page count, external links, and visits) and economic variables (total expenditures, expenditures on printed and electronic books, and physical visits). The results indicate that the variety of URL syntaxes is wide, diverse and complex, which produces a misrepresentation of academic library web resources and reduces the accuracy of web analysis. On the other hand, institutional and web data indicators are not highly correlated. Better results are obtained by correlating total library expenditures with URL mentions measured by Google (r= 0.546) and visits measured by Compete (r= 0.573), respectively. Because correlation values obtained are not highly significant, we estimate such correlations will increase if users can avoid linkage problems (due to the complexity of URLs) and gain direct access to log files (for more accurate data about visits).

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