@article{chatgpt-search,

title = {ChatGPT Search as a tool for scholarly tasks: evolution or devolution?},

author = {Cristina I. Font-Julian and Enrique Orduña-Malea and Lluís Codina},

doi = { https://doi.org/10.3145/infonomy.24.059},

issn = {2990-2290},

year  = {2024},

date = {2024-11-26},

journal = {Infonomy},

volume = {2},

number = {5},

pages = {15},

abstract = {ChatGPT Search was launched on October 31 by OpenAI as a new AI-powered search engine. Among its features, it stands out for its ability to retrieve information from various online sources, including scholarly databases, which potentially allows the use of this tool for academic tasks, both quantitative and qualitative. To test its features, five academic tasks are designed: two quantitative (collecting hit count estimates from Google Search and scraping bibliometric indicators from ResearchGate); two qualitative tasks (performing a narrative synthesis of an academic topic and generating a brief academic author profile), and a mixed task (identifying, collecting and describing a list of publications from Google Scholar Profiles). The results show the inability of ChatGPT Search to conduct quantitative tasks correctly, fabricating the results (hallucination). Qualitative tasks are performed with better results; however, errors are detected, which prevent recommending the tool without manual analysis and refinement. Finally, the ability to generate links to scientific publications can open up competition among academic sites to be mentioned in the ChatGPT Search responses, giving rise to Academic Generative Engine Optimization (A-GEO).},

keywords = {A-GEO, Academic Generative Engine Optimization, Academic Tasks, AI, ChatGPT, ChatGPT Search, Generative Artificial Intelligente, Information Retrieval, Link Analysis, Narrative Synthesis, Quantitative vs Qualitative, Scholarly Tasks, Search Engines, Web Search},

pubstate = {published},

tppubtype = {article}

}

@article{Orduña-Malea2024,

title = {Open access publications drive few visits from Google Search results to institutional repositories},

author = {Enrique Orduña-Malea and Cristina I. Font-Julian and Jorge Serrano-Cobos},

doi = {https://doi.org/10.1007/s11192-024-05175-0},

issn = {1588-2861},

year  = {2024},

date = {2024-10-12},

urldate = {2024-10-12},

journal = {Scientometrics},

abstract = {Given the importance of Google Search in generating visits to institutional repositories (IR), a lack of visibility in search engine results pages can hinder the possibility of their publications being found, read, downloaded, and, eventually, cited. To address this, institutions need to evaluate the visibility of their repositories to determine what actions might be implemented to enhance them. However, measuring the search engine optimization (SEO) visibility of IRs requires a highly accurate, technically feasible method. This study constitutes the first attempt to design such a method, specifically applied here to measuring the IR visibility of Spain’s national university system in Google Search based on a set of SEO-based metrics derived from the Ubersuggest SEO tool. A comprehensive dataset spanning three months and comprising 217,589 bibliographic records and 316,899 organic keywords is used as a baseline. Our findings show that many records deposited in these repositories are not ranked among the top positions in Google Search results, and that the most visible records are mainly academic works (theses and dissertations) written in Spanish in the Humanities and Social Sciences. However, most visits are generated by a small number of records. All in all, our results call into question the role played by IRs in attracting readers via Google Search to the institutions’ scientific heritage and serve to underscore the prevailing emphasis within IRs on preservation as opposed to online dissemination. Potential improvements might be achieved using enhanced metadata schemes and normalized description practices, as well as by adopting other actionable insights that can strengthen the online visibility of IRs. This study increases understanding of the role played by web indicators in assessing the web-based impact of research outputs deposited in IRs, and should be of particular interest for a range of stakeholders, including open access and open science advocates, research agencies, library practitioners, repository developers, and website administrators.},

keywords = {Academic SEO, Altmetrics, Institutional Repositories, Open Access, Spain, Universities},

pubstate = {published},

tppubtype = {article}

}

@article{Font-Julian2023,

title = {Margarita Salas: un gran nombre para un contrato postdoctoral mejorable},

author = {Cristina I. Font-Julian and Enrique Orduña-Malea},

doi = {https://doi.org/10.3145/thinkepi.2023.e17a06},

issn = {2564-8837},

year  = {2023},

date = {2023-04-03},

journal = {Anuario ThinkEPI},

volume = {17},

number = {e17a06},

abstract = {One year after the incorporation of Margarita Salas researchers in universities and research cen-tres thanks to the plan for the requalification of the Spanish university system carried out by the Ministry of  Universities,  this  work  compiles  the  main  problems  and  limitations  of  this  postdoctoral  contract  and  outlines some possible solutions for future calls with similar characteristics.},

keywords = {Job insecurity, Ministry of Universities, Postdoctoral contracts, Science Management, Spain, Universities, Young researchers},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Is research funding always beneficial? A cross-disciplinary analysis of UK research 2014–20},

author = {Mike Thelwall and Kayvan Kousha and Mashid Abodli and Emma Stuart and Meiko Makita and Cristina I. Font-Julian and Paul Wilson and Jonathan Levitt},

editor = {Ludo Waltman},

doi = {https://doi.org/10.1162/qss_a_00254},

issn = {2641-3337},

year  = {2023},

date = {2023-03-25},

urldate = {2023-03-25},

journal = {Quantitative Science Studies},

volume = {4},

issue = {2},

pages = {501-534},

abstract = {While funding is essential for some types of research and beneficial for others, it may constrain academic choice and creativity. Thus, it is important to check whether it ever seems unnecessary. Here we investigate whether funded UK research tends to be higher quality in all fields and for all major research funders. Based on peer review quality scores for 113,877 articles from all fields in the UK’s Research Excellence Framework (REF) 2021, we estimate that there are substantial disciplinary differences in the proportion of funded journal articles, from Theology and Religious Studies (16%+) to Biological Sciences (91%+). The results suggest that funded research is likely to be of higher quality overall, for all the largest research funders, and for 30 out of 34 REF Units of Assessment (disciplines or sets of disciplines), even after factoring out research team size. There are differences between funders in the average quality of the research supported, however. Funding seems particularly associated with higher research quality in health-related fields. The results do not show cause and effect and do not take into account the amount of funding received, but are consistent with funding either improving research quality or being won by high-quality researchers or projects.},

keywords = {Academic Careers, Research Funding, Research Grants, Research Quality, Scientometrics},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Are patents linked on Twitter? A case study of Google patents},

author = {Enrique Orduña-Malea and Cristina I. Font-Julian},

doi = {https://doi.org/10.1007/s11192-022-04519-y},

year  = {2022},

date = {2022-10-10},

urldate = {2022-10-10},

journal = {Scientometrics},

volume = {127},

pages = {6339–6362},

abstract = {This study attempts to analyze patents as cited/mentioned documents to better understand the interest, dissemination and engagement of these documents in social environments, laying the foundations for social media studies of patents (social Patentometrics).Particularly, this study aims to determine how patents are disseminated on Twitter by analyzing three elements: tweets linking to patents, users linking to patents, and patents linked from Twitter. To do this, all the tweets containing at least one link to a full-text patent available on Google Patents were collected and analyzed, yielding a total of 126,815 tweets (and 129,001 links) to 86,417 patents. The results evidence an increase of the number of linking tweets over the years, presumably due to the creation of a standardized patent URL ID and the integration of Google Patents and Google Scholar, which took place in 2015. The engagement achieved by these tweets is limited (80.2% of tweets did not attract likes) but increasing notably since 2018. Two super-publisher twitter bot accounts (dailypatent and uspatentbot) are responsible of 53.3% of all the linking tweets, while most accounts are sporadic users linking to patent as part of a conversation. The patents most tweeted are, by far, from United States (87.5% of all links to Google Patents), mainly due to the effect of the two super-publishers. The impact of patents in terms of the number of tweets linking to them is unrelated to their year of publication, status or number of patent citations received, while controversial and media topics might be more determinant factors. However, further research is needed to better understand the topics discussed around patents on Twitter, the users involved, and the metrics attained. Given the increasing number of linking users and linked patents, this study finds Twitter as a relevant source to measure patent-level metrics, shedding light on the impact and interest of patents by the broad public.},

keywords = {Altmetrics, Link Analysis, Patent, Social Media Metrics, Social Patentometrics, Twitter},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Which types of online resource support US patent claims?},

author = {Cristina I. Font-Julian and José-Antonio Ontalba-Ruipérez and Enrique Orduña-Malea and Mike Thelwall},

url = {https://crifonju.upv.edu.es/wp-content/uploads/2022/02/Graphical-abstract.pdf},

doi = {10.1016/j.joi.2021.101247},

issn = {1751-1577},

year  = {2022},

date = {2022-01-05},

urldate = {2022-01-05},

journal = {Journal of Informetrics},

volume = {16},

number = {101247},

issue = {2022},

pages = {14},

abstract = {Patents are key documents to support the commercial exploitation of inventions. Patent docu- ments must claim inventiveness, industrial application, and novelty to be granted and may use citations and URLs to support these claims as well as to explain their ideas. Although there is much research into the citations used to support inventions, almost nothing is known about the cited URLs. This may hinder inventors and evaluators from deciding which URLs are appropriate. To investigate this issue, all 3,133,247 patents granted by the United States Patent and Trademark Office (USPTO) from 2008 to 2018 were investigated, and 2,719,705 URLs (patent outlinks) were automatically extracted using heuristics, and analyzed using link analyses techniques. A minority of patents included URLs (17.1%), with the percentage increasing over time. The inclusion of URLs differs between disciplines, with Physics (especially the subcategory Computation) having the most URLs per patent. Patents are generally embedded in the “other citations” patent section (referring to academic publications) and the “description” section (e.g., supplementary infor- mation and definitions). Online content-oriented resources (e.g., Wayback Machine, Wikipedia, YouTube), academic bibliographic databases (e.g., IEEE Xplore, Microsoft Academic, PubMed, CiteSeerX) and technological companies (e.g., IBM, Amazon, Microsoft) are often linked from USPTO patents. These findings show the broad roles that URLs can play when supporting a patent claim. Finally, in order to avoid bad practices found in the inclusion of URLs in patents, a list of recommendations to cite online resources from patents is provided.},

keywords = {Informetrics, Link Analysis, Patent, Patent Analysis, United States Patent and Trademark Office online resources},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Masters of Wine on Twitter: presence, activity, impact and community structure},

author = {Enrique Orduña-Malea and Cristina I. Font-Julian and José-Antonio Ontalba-Ruipérez and Raúl Compés-López},

doi = {doi.org/10.36253/wep-9055},

issn = {2112-9774},

year  = {2021},

date = {2021-04-17},

journal = {Wine Economics and Policy},

volume = {10},

issue = {1},

pages = {73-88},

abstract = {Globalisation, the Internet and social media have changed the kind of actors with influence in the wine industry and the way these actors create signals to communicate credible information about experience and trust attributes. Among the most prestigious experts in the world of wine are the Masters of Wine (MW). Although initially devoted to international trade, they have spread their activities and their opinion is more and more appreciated by producers and consumers. The main objective of this article is to determine this community of experts’ behaviour on Twitter. In order to do so, four factors (presence, activity, impact and community) have been considered. All Twitter profiles belonging to users awarded with the MW qualification were identified and analysed. In addition, a set of 35,653 tweets published by the MWs were retrieved and analysed through descriptive statistics. The results show MWs on Twitter as high attractors (number of followers), moderate publishers (original contents published), moderate influencers (number of likes and retweets), and low interactors (number of friends and mentions to other users). These findings reveal that the MW community is not using Twitter to gain or reinforce their reputation as an accredited expert in the wine industry, giving more influential space on Twitter to consumers and amateurs.},

keywords = {Informetrics, Social Media, Twitter, Wine, Wine Experts, Wine Industry},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Covid-19: análisis métrico de vídeos y canales de comunicación en YouTube},

author = {Enrique Orduña-Malea and Cristina I. Font-Julian and José-Antonio Ontalba-Ruipérez},

doi = {10.3145/epi.2020.jul.01},

issn = {1699-2407},

year  = {2020},

date = {2020-05-17},

urldate = {2020-05-17},

journal = {Profesional de la Información},

volume = {29},

number = {4},

pages = {e290401},

abstract = {El objetivo de este trabajo es determinar el volumen de vídeos sobre Covid-19 publicados y difundidos a través de <em>YouTube</em> y relacionados directa o indirectamente con el territorio nacional español, caracterizar su impacto (en términos de visualizaciones, <em>likes</em> y comentarios recibidos), y finalmente categorizar los canales a través de los cuales se han difundido. Para ello se han analizado 39.531 vídeos publicados entre el 1 enero y el 30 de abril de 2020. Los resultados muestran que el número de vídeos sobre Covid-19 aumentaron a partir del establecimiento del estado de alarma en España y, poco a poco, han ido disminuyendo en el tiempo, con ciertos repuntes vinculados a decisiones políticas. Los vídeos logran en promedio un gran número de visualizaciones, <em>likes/dislikes</em> y comentarios, y han sido publicados principalmente por medios de comunicación. Los vídeos relacionados con blogs y entretenimiento son muy numerosos pero con menor impacto. Los vídeos pertenecientes a las categorías de <em>Educación</em> y <em>Ciencia y Tecnología</em> son menos numerosos pero con un alto impacto, especialmente en visualizaciones. De forma complementaria, se concluye que los criterios de ordenación de <em>YouTube</em> no son lo suficientemente precisos como para ser utilizados en estudios informétricos sin una alta carga de trabajo en limpieza de datos. Así mismo, la existencia de canales que aplican estrategias engañosas de posicionamiento dificulta la realización de este tipo de estudios.},

keywords = {Coronavirus, Covid-19, Health Information, Informetrics, Pandemics, Spain, Video, YouTube},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Universidades en Google: hacia un modelo de análisis multinivel del posicionamiento web académico},

author = {Javier González-Llinares and Cristina I. Font-Julian and Enrique Orduña-Malea},

doi = {10.3989/redc.2020.2.1691},

isbn = {1988-4621},

year  = {2020},

date = {2020-04-17},

urldate = {2020-04-17},

journal = {Revista Española De Documentación Científica},

volume = {43},

number = {2},

pages = {e260},

abstract = {Se propone un modelo de análisis del posicionamiento web de universidades basado en un vocabulario de palabras clave categorizadas según las distintas misiones universitarias, que se aplica a una universidad (Universitat Politècnica de València) para comprobar su idoneidad. A partir de un vocabulario de 164 palabras clave se construyeron 290 consultas web que fueron ejecutadas en Google, recopilando los 20 primeros resultados obtenidos para cada consulta. Los resultados confirman que las universidades obtienen un posicionamiento web variable en función de la dimensión vinculada a la consulta web y que las páginas web vinculadas a la docencia (especialmente Grados) son las que mejor posicionan, incluso para consultas web orientadas a investigación. Con todo, se observa un posicionamiento bajo no sólo para la UPV sino para las universidades públicas presenciales españolas (sólo el 27% del total de resultados en el Top 20 corresponde a alguna de estas universidades). Se concluye que el análisis multinivel es necesario para estudiar el posicionamiento web de las universidades y que el modelo propuesto es viable y escalable. No obstante, se han identificado ciertas limitaciones (dependencia del vocabulario utilizado y alta variabilidad de datos) que deben tenerse en cuenta en el diseño de este tipo de modelos de análisis.},

keywords = {Academic SEO, Cybermetrics, Evaluation Model, Google, Search Engines, Search Engines Optimization, SEO, Universities, Web positioning, Web Visibility, Webometrics},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Hit count estimate variability for website-specific queries in search engines: The case for rare disease association websites},

author = {Cristina I. Font-Julian and Enrique Orduña-Malea and José-Antonio Ontalba-Ruipérez},

doi = {10.1108/AJIM-10-2017-0226},

issn = {2050-3806},

year  = {2018},

date = {2018-02-07},

urldate = {2018-02-07},

journal = {Aslib Journal of Information Management},

volume = {70},

number = {2},

pages = {192-213},

abstract = {Purpose

The purpose of this paper is to determine the effect of the chosen search engine results page (SERP) on the website-specific hit count estimation indicator.



Design/methodology/approach

A sample of 100 Spanish rare disease association websites is analysed, obtaining the website-specific hit count estimation for the first and last SERPs in two search engines (Google and Bing) at two different periods in time (2016 and 2017).



Findings

It has been empirically demonstrated that there are differences between the number of hits returned on the first and last SERP in both Google and Bing. These differences are significant when they exceed a threshold value on the first SERP.



Research limitations/implications

Future studies considering other samples, more SERPs and generating different queries other than website page count (<site>) would be desirable to draw more general conclusions on the nature of quantitative data provided by general search engines.



Practical implications

Selecting a wrong SERP to calculate some metrics (in this case, website-specific hit count estimation) might provide misleading results, comparisons and performance rankings. The empirical data suggest that the first SERP captures the differences between websites better because it has a greater discriminating power and is more appropriate for webometric longitudinal studies.



Social implications

The findings allow improving future quantitative webometric analyses based on website-specific hit count estimation metrics in general search engines.



Originality/value

The website-specific hit count estimation variability between SERPs has been empirically analysed, considering two different search engines (Google and Bing), a set of 100 websites focussed on a similar market (Spanish rare diseases associations), and two annual samples, making this study the most exhaustive on this issue to date.



},

keywords = {Bing, Google, Hit Count Estimates, Rare Diseases, Search Engines, Website Page Count},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Comunicación Científica (XXXVIII). Cómo hacer una estrategia "social media" para pediatras (V). Academic SEO a través de Google Scholar.},

author = {Jorge Serrano-Cobos and Cristina I. Font-Julian and J. González de Dios and R. Aleixandre-Benavent},

isbn = {978-84-9905-261-8},

year  = {2016},

date = {2016-07-07},

urldate = {2016-07-07},

journal = {Acta Pediátrica},

volume = {74},

number = {10},

pages = {266-272},

abstract = { La interacción de los científicos en sus conductas de búsqueda de información científica ha cambiado en los últimos años, con la utilización cada vez más de Google Scholar como fuente principal de indagación. Por tanto, para mejorar el impacto científico es necesario entender cómo mejorar la encontrabilidad de la producción científica en este buscador, por lo que en este artículo se desglosa una selección de factores y acciones de comunicación que llevar a cabo con el fin de mejorar la presencia online de los pediatras y apoyar el impacto de su producción digital.},

keywords = {Academic SEO, Google Scholar, Metrics, Scientific Impact, Scientific Visibility, Search Engines Optimization},

pubstate = {published},

tppubtype = {article}

}