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This paper explores the procedural meaning of the Spanish adverb apenas , proposing that it carries the procedural meaning of right-hand APPROACHING. This procedural meaning effectively accounts for various interpretations and argumentative orientations of apenas in different contexts. The analysis demonstrates that apenas consistently implies a closeness or minimality, whether in quantitative or temporal domain. The procedural meaning also explains the negative argumentative orientation of apenas. Therefore, the different meanings of apenas can be analyzed in a holistic way. Through this analysis, the study aims to contribute to a deeper understanding of adverbial usage in Spanish and potentially guide analogous investigations in other languages. • The Spanish adverb apenas carries a procedural meaning. • The procedural meaning can offer a holistic analysis of this adverb. • The procedural meaning also explains the negative argumentative orientation of apenas. [ABSTRACT FROM AUTHOR]

Text mining has led to growth in sentiment analysis (SA) across various research disciplines. The pandemic has provided a unique and special context for analysing students’ written expression. We utilised comments from a survey conducted during the pandemic to create a corpus for SA. The corpus comprises 25,197 words extracted from over 600 comments in Spanish, collected during a survey that lasted around 20 days. We aim to detect sentiments and emotions from this corpus using SA. However, some essential and little-discussed issues in literature should be addressed, such as its relationship with post-cognitivist theory. This paper uses the post-cognitivist approach to analyse emotions and sentiments through SA with the Spanish lexicon in the economics of education. Literature in this area needs further development, especially in Spanish. The article shows that the emotions and sentiments of students in challenging situations can be identified through a corpus of student comments. However, specific elements should be considered while interpreting emotions and sentiments within the framework of post-cognitivism methodologies. Recognising that the human experience is a complex interaction, it is essential to consider the emotional nuances within the context in which they develop. Addressing this issue from the post-cognitivist approach is one of several ways to carry out this task. Using SA and emotions to analyse a text corpus is still helpful for researchers who follow the post-cognitivist approach. However, combining this technique with other qualitative and in-depth computational methods is essential to fully understanding the emotional experiences within their respective contexts. [ABSTRACT FROM AUTHOR]

Sign language serves as the primary mode of communication for the deaf community. With technological advancements, it is crucial to develop systems capable of enhancing communication between deaf and hearing individuals. This paper reviews recent state-of-the-art methods in sign language recognition, translation, and production. Additionally, we introduce a rule-based system, called ruLSE, for generating synthetic datasets in Spanish Sign Language. To check the usefulness of these datasets, we conduct experiments with two state-of-the-art models based on Transformers, MarianMT and Transformer-STMC. In general, we observe that the former achieves better results (+3.7 points in the BLEU-4 metric) although the latter is up to four times faster. Furthermore, the use of pre-trained word embeddings in Spanish enhances results. The rule-based system demonstrates superior performance and efficiency compared to Transformer models in Sign Language Production tasks. Lastly, we contribute to the state of the art by releasing the generated synthetic dataset in Spanish named synLSE. [ABSTRACT FROM AUTHOR]

The presence of English borrowings is becoming frequent in Spanish. This paper deals with the use of Anglicisms, including some cases of pseudo-Anglicisms and hybrid formations, in sports. The analysis of the digital edition of various Spanish newspapers, using the Anglicisms search tool 'Observatorio Lázaro,' has revealed a variety of functions that are fulfilled by these English(-looking) lexical items, such as their metaphorical uses. This study provides examples of new compound terms as well as hybrid formations and clippings, among others, some of which intend to have certain pragmatic meanings, e.g. being euphemistic or producing ironic and humorous effects on the reader. In addition, it is worth mentioning the usage of English football nicknames that seem to be getting more and more familiar to the Spanish sports audience. The orthographic inconsistency of many of the collected sport-related words is also examined and evidences the recent incorporation of these terms into Spanish. [ABSTRACT FROM AUTHOR]

Author profiling consists of extracting their demographic and psychographic information by examining their writings. This information can then be used to improve the reader experience and to detect bots or propagators of hoaxes and/or hate speech. Therefore, author profiling can be applied to build more robust and efficient Knowledge-Based Systems for tasks such as content moderation, user profiling, and information retrieval. Author profiling is typically performed automatically as a document classification task. Recently, language models based on transformers have also proven to be quite effective in this task. However, the size and heterogeneity of novel language models, makes it necessary to evaluate them in context. The contributions we make in this paper are four-fold: First, we evaluate which language models are best suited to perform author profiling in Spanish. These experiments include basic, distilled, and multilingual models. Second, we evaluate how feature integration can improve performance for this task. We evaluate two distinct strategies: knowledge integration and ensemble learning. Third, we evaluate the ability of linguistic features to improve the interpretability of the results. Fourth, we evaluate the performance of each language model in terms of memory, training, and inference times. Our results indicate that the use of lightweight models can indeed achieve similar performance to heavy models and that multilingual models are actually less effective than models trained with one language. Finally, we confirm that the best models and strategies for integrating features ultimately depend on the context of the task. • Study of large language models for conducting Author Profiling in Spanish. • Feature integration improves the performance of large language models. • Interpretability of profiles using linguistic features. • Hyperlinks and hashtag are strong features when discerning between bots and humans. • Stylometry is the linguistic category most relevant in Author Profiling. [ABSTRACT FROM AUTHOR]