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Analysis of institutional authors

Pilicita AAuthorBarra EAuthor
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Article

Using of Transformers Models for Text Classification to Mobile Educational Applications

Publicated to:Ieee Latin America Transactions. 21 (6): 730-736 - 2023-06-01 21(6), DOI: 10.1109/TLA.2023.10172138

Authors: Garrido, AP; Arias, EB

Affiliations

Univ Politecn Madrid, Madrid, Spain - Author
Universidad Politécnica de Madrid - Author

Abstract

In Q2 2022, educational apps were the second most popular category on the Google Play Store, accounting for 10.47% of the apps available worldwide. This work explores the application of five BERT-based pre-trained models with the Transformers architecture to classify mobile educational applications. These five models are according to the knowledge field: bert-base-cased, bert-base-uncased, roberta-base, albert-base-v2 and distilbert-base-uncased. This study uses a dataset with educational apps of Google Play, this dataset was enriched with description and category because it lacked this information. In all models, a tokenizer and fine-tuning works were applied for training in the classification task. After training the data, the testing phase was performed in which the models had to go through four training epochs to obtain better results: roberta-base with 81% accuracy, bert-base-uncased with 79% accuracy, bert-base-cased obtained 80% accuracy, albert-base-v2 obtained 78% accuracy and distilbert-base-uncased obtained 76% accuracy.

Keywords
bidirectional encoder representations from transformersieee transactionsinternetmulticlass text classificationnatural language processingrecurrent neural networkstext categorizationtrainingtransformersBit error rateNatural language processing, multiclass text classification, transformers, bidirectional encoder representations from transformers.

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Ieee Latin America Transactions due to its progression and the good impact it has achieved in recent years, according to the agency Scopus (SJR), it has become a reference in its field. In the year of publication of the work, 2023, it was in position , thus managing to position itself as a Q2 (Segundo Cuartil), in the category Computer Science (Miscellaneous). Notably, the journal is positioned en el Cuartil Q3 for the agency WoS (JCR) in the category Computer Science, Information Systems.

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 2025-05-02:

  • Google Scholar: 2
  • WoS: 2
  • Scopus: 4
  • OpenCitations: 4
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 2025-05-02:

  • 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: 17 (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.
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 (PILICITA GARRIDO, ANABEL) and Last Author (BARRA ARIAS, ENRIQUE).