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Analysis of institutional authors

Huertas-Tato JCorresponding AuthorMartín García, AlejandroAuthorCamacho DAuthor

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July 31, 2023
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BERTuit: Understanding Spanish language in Twitter with transformers

Publicated to: EXPERT SYSTEMS. 40 (9): - 2023-11-01 40(9), DOI: 10.1111/exsy.13404

Authors:

Huertas-Tato, J; Martín, A; Camacho, D
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Affiliations

Univ Politecn Madrid, Dept Informat, Madrid 28031, Spain - Author
Universidad Politécnica de Madrid - Author

Abstract

The appearance of complex attention-based language models such as BERT, RoBERTa or GPT-3 has allowed to address highly complex tasks in a plethora of scenarios. However, when applied to specific domains, these models encounter considerable difficulties. This is the case of Social Networks such as Twitter, an ever-changing stream of information written with informal and complex language, where each message requires careful evaluation to be understood even by humans given the important role that context plays. Addressing tasks in this domain through Natural Language Processing involves severe challenges. When powerful state-of-the-art multilingual language models are applied to this scenario, language specific nuances get lost in translation. To face these challenges we present BERTuit, the largest transformer proposed so far for Spanish language, pre-trained on a massive dataset of 230 M Spanish tweets using RoBERTa optimization. Our motivation is to provide a powerful resource to better understand Spanish Twitter and to be used on applications focused on this social network, with special emphasis on solutions devoted to tackle the spreading of misinformation in this platform. BERTuit is evaluated on several tasks and compared against M-BERT, XLM-RoBERTa and XLM-T, very competitive multilingual transformers. The utility of our approach is shown with applications, in this case: an unsupervised methodology to visualize groups of hoaxes; and supervised profiling of authors spreading disinformation.
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Keywords

online social networkstransformerstwitterMisinformationOnline social networksTransformersTwitter

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal EXPERT SYSTEMS due to its progression and the good impact it has achieved in recent years, according to the agency WoS (JCR), it has become a reference in its field. In the year of publication of the work, 2023, it was in position 41/144, thus managing to position itself as a Q2 (Segundo Cuartil), in the category Computer Science, Theory & Methods. Notably, the journal is positioned en el Cuartil Q2 para la agencia Scopus (SJR) en la categoría Control and Systems Engineering.

Independientemente del impacto esperado determinado por el canal de difusión, es importante destacar el impacto real observado de la propia aportación.

Según las diferentes agencias de indexación, el número de citas acumuladas por esta publicación hasta la fecha 2026-04-27:

  • Google Scholar: 4
  • WoS: 3
  • Scopus: 5
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Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2026-04-27:

  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 37 (PlumX).

It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

  • The work has been submitted to a journal whose editorial policy allows open Open Access publication.
  • Assignment of a Handle/URN as an identifier within the deposit in the Institutional Repository: https://oa.upm.es/88862/

As a result of the publication of the work in the institutional repository, statistical usage data has been obtained that reflects its impact. In terms of dissemination, we can state that, as of

  • Views: 165
  • Downloads: 74
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Leadership analysis of institutional authors

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: First Author (HUERTAS TATO, JAVIER) and Last Author (CAMACHO FERNANDEZ, DAVID).

the author responsible for correspondence tasks has been HUERTAS TATO, JAVIER.

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