Papers reviewed and determined not to be word norm studies. Use the flag icon to report errors or suggest re-inclusion.
18265 papers
This article explores the development of a linguistic database for the translation of Uzbek grammatical forms into English. The study investigates translation equivalence and divergence at the grammatical level through the lens of contrastive linguistics and computational linguistics. Affixal forms, auxiliary verbs, modal expressions, and syntactic structures in Uzbek are systematically matched with their grammatical and semantic equivalents in English. Based on this mapping, a modern linguistic platform named UzEngGram.uz has been developed. The paper outlines stages of grammatical identification, classification, translation modeling using a parallel corpus, automation through NLP tools, and the creation of a lexical-grammatical database. It is further argued that the resulting resource serves as a critical tool for machine translation systems, linguistic analysis, and educational applications.
Stylistics has long been recognized as the linguistic study of texts. In its contemporary understanding, however, stylistics extends beyond the analysis of linguistic components to examine how language choices convey meaning and produce aesthetic effects. Foregrounding is one of the central concepts in stylistic analysis. It refers to a technique through which a writer or poet deliberately deviates from or parallels conventional language patterns in order to attract the reader’s attention and establish a distinctive style. The long poem Shikwā by Muḥammad Iqbāl has remained an enduring favorite among Urdu literary critics and has increasingly drawn the attention of stylisticians. This paper seeks to explore how Iqbāl’s poetic style emerges through the systematic making and breaking of linguistic norms. It specifically examines the use of linguistic parallelism and linguistic deviation as key foregrounding devices that contribute to the poem’s stylistic richness. By analyzing these stylistic features, the study demonstrates how Iqbāl transforms language into a powerful expressive medium, enabling Shikwā to achieve both emotional depth and intellectual impact. The paper argues that the conscious manipulation of linguistic patterns not only enhances the poem’s aesthetic appeal but also secures its status as a timeless masterpiece of Urdu poetry.
This research is motivated by concerns about the decline in communication quality and character values among youth due to the use of slang language that does not adhere to proper linguistic norms, particularly through the widespread use of social media. The aim of this study is to examine the influence of slang language used on social media on the development of character values among female students at STITMA Yogyakarta, as well as to explore their perspectives on this phenomenon in daily life. This study employs a quantitative approach with a correlational method. Data collection techniques include questionnaires, interviews, and documentation. The population consists of fourth- and sixth-semester female students from the Islamic Education (PAI) and Arabic Education (PBA) programs, with a sample of 75 students selected using proportionate stratified random sampling. The data were analyzed using validity, reliability, normality, homogeneity tests, and hypothesis testing through the Pearson Product Moment correlation test. The results show that the calculated r-value of 0.967 is greater than the critical r-value of 0.2272, indicating a significant and positive influence between the use of slang language and character values. Thus, slang language is proven to impact the character development of female students in today’s digital era.
The development of digital technology has transformed communication patterns among young people, particularly through social media. However, the use of the Indonesian language by junior high school students in digital spaces often neglects linguistic norms and lacks politeness. This community service project aimed to educate students of SMPIT Al-Hijrah 2 Deli Serdang on how to use Indonesian properly, accurately, and politely in digital communication. The method involved initial observation, development of a contextual learning module based on social media content, implementation of interactive training, and follow-up evaluation and mentoring. The results indicate a significant improvement in students’ understanding of language norms and online communication ethics. Students became more aware in choosing appropriate diction, composing grammatically correct sentences, and maintaining polite interactions in social media posts and comments. Post-training mentoring also showed consistency in the students’ application of polite language in their digital interactions. This program demonstrates that language education integrated with digital literacy and character-building can shape ethical and productive communication behaviors among junior high school students. Such education is recommended to be continuously implemented as part of school literacy programs.
The article is devoted to the study of the current topic of modern communication– virtual language personality, and the description of lexical and semantic features of virtual language personality in Internet communication. The issue of dynamic changes in the Kazakh vocabulary introduced through Internet communication has become especially relevant in recent years. The research work began with a review of the research of domestic and foreign scientists, the features and main trends were described. During the review of scientific papers analyzing the discourse of the social network and its text, the fundamental concepts were identified and the necessary conclusions were drawn, which guided us. The purpose of the study Is to consider the set of lexical and semantic properties of social network usages. The article notes that the main feature of communication in Kazakh-speaking social networks is the replacement of a real participant by a participant in virtual communication. We have done analysis of the structure, lexical and grammatical characteristics of Kazakh texts collected from social networks. The features of the texts of the discourse of social networks were described. It is mentioned that texts in social networks are not a source of knowledge, they are news or entertainment information, and accordingly they should have brief but rich information, the information in the text is transmitted not only by writing letters, but also by pictures, audio and video recordings. Examples from Facebook and WhatsApp networks were given as research materials. The study revealed the use of Facebook language terms in Kazakh texts, an increase in the activity of foreign words, a lexical-syntactic combination of foreign and native words, a combination of words without a lexical combination, etc. As a result, on the basis of the collected materials, grammatical (morphological, syntactic) features of Kazakh texts in the social network were divided into groups and a linguistic analysis was carried out. In modern public consciousness, linguistic research has become relevant, defining the linguistic image of a social network as a means of implementing linguistic communication. In this regard, it is very important to improve the language skills of network users.
Ce travail vise à explorer l’effet facilitateur d’une langue romane (français ou espagnol) et de l’anglais dans l’apprentissage lexical d’une autre langue romane (espagnol ou français) dans un contexte universitaire. D’une part, l’appartenance à la même famille des langues romanes facilite largement l’acquisition des connaissances linguistiques. D’autre part, un étudiant ayant réussi l’examen d’entrée à l’université est censé avoir atteint au moins le niveau indépendant (B2) en anglais, tandis qu’un étudiant spécialisé en langues étrangères peut atteindre un niveau autonome (C1), selon les normes du programme d’anglais dans le cadre de la scolarité obligatoire publiés par le ministère de l’Éducation de la République populaire de Chine (2018). Un tel niveau de compétence en anglais joue nécessairement un rôle non négligeable dans l’apprentissage d’une autre langue indo-européenne. L’étude repose sur une classification des catégories d’unités transparentes du point de vue d’apprenants sinophones, ainsi que sur la comparaison de trois lexiques: un lexique espagnol élaboré à partir des manuels scolaires destinés aux étudiants chinois; un lexique français construit selon la même logique; et un lexique espagnol extrait d’un corpus naturel issu du projet iRead4Skills, destiné aux apprenants natifs. Ces lexiques, différenciés par la langue cible et le public visé, offrent une vue d’ensemble pertinente pour analyser la transparence lexicale dans l’acquisition du vocabulaire roman chez les apprenants sinophones.
We are using a Wikibase instance (https://lilamorph.wikibase.cloud) for publishing a Latin verb forms dataset, with the final goal of enriching Wikidata Latin lexemes, and for corpus annotation (matching tokens in morphologically annotated corpora to Wikibase forms). Building on the PrinParLat lexicon of Latin verb principal parts, we generate the complete set of inflected forms for over 8,000 verbs, encoded as RDF in a dedicated Wikibase instance. These data are linked to the Index Thomisticus Treebank (ITTB), whose morphologically annotated tokens are related to corresponding forms based on segmental identity, lemma alignment, and mapped morphological features. Our method achieves over 95% coverage of ITTB verbal tokens, demonstrating the robustness of our generation and linking pipeline even for Medieval Latin data. By aligning Paralex, Wikidata, and LiLa ontologies, we ensure semantic interoperability and facilitate future integration into Wikidata. Beyond Latin, this workflow provides a reproducible model for linking inflectional paradigms and corpus attestations in other languages. With the different forms lexica built on our Wikibase instance, we are now in the position to contribute to a discussion in the Wikidata community, comparing different options of representation of inflected forms. We would like to highlight corpus token linking as central use case for Wikibase forms, which entails to adopt the data model that caters best for that application, namely a separate listing of orthographically identical but morphologically ambiguous forms. Having chosen Wikibase as platform for the experiments presented here, all datasets remain now ready for intervention of human or algorithmic users, who would mark ambiguous links (from token to form, or from token to lila lemma), as “preferred” or “deprecated”, so that the ambiguity is resolved.
The article describes intra- and extra-linguistic factors that influence the stability of the onymic space of the Ukrainian language. Intra-linguistic factors are the creation of a certain proper name according to its inherent derivational model; the correspondence of a particular onymic to the formed linguistic norm. Extra-linguistic factors are the level of linguistic, spiritual and political culture of society and its national consciousness. This influence is most pronounced on two classes of onymic vocabulary — anthroponyms and toponyms, as well as on toponymic derivatives — the names of the inhabitants of the corresponding settlement (katoikonyms) and derived adjectives (adjectonyms). It is specially noted of the three-component anthroponymic formula (first name, patronymic, surname) in modern Ukrainian official speech; the elimination of variation in the declension of Ukrainian surnames of the masculine gender with the possessive suffix -iB. It is shown that main means of creating katoikonyms in the Ukrainian language are the suffixes -u-i (plural), -eub, -K-a (singular). Possible functioning of parallel catoikonymic forms with suffixes -a-i (-eab, -K-a) h -aH-H / -hh-h (-aH-HH, -aH-K-a / -hh-hh, -HH-K-a). The paper deals with problem of establishing derivational models of adjectonyms and their normalization. The author considers that it is necessary to carefully study the historical patterns of the creation and use of adjectonyms in the Ukrainian language, as well as to take into account local traditions. The destructive impact on the Ukrainian oikonymic space of numerous unmotivated ideological renamings of the Soviet era and artificial formations with a Russian-language structure is analyzed. The author shows that it is necessary to cleanse the Ukrainian oikonomika and urbanonymika of such names.
This paper explores how people’s lifestyles are reflected within linguistic anthropocentric paradigms, emphasizing the central role of human experience in shaping language. Anthropocentrism frames language as a dynamic system through which individuals negotiate identities, communicate cultural norms, and establish social hierarchies. Adopting insights from cognitive linguistics, sociolinguistics, and discourse analysis, the study examines the conceptualization processes that encode lifestyle values into everyday speech, metaphors, and broader discursive practices. Particular attention is paid to the ways in which cultural concepts, identity markers, and social structures manifest in lexical choices and communicative strategies. The analysishighlights how metaphors, identity expressions, and discourse patterns serve as windows into a community’s lifestyle priorities and norms, revealing the interplay between language, cognition, and socio-cultural contexts. Finally, the paper underscores thesignificance of recognizing power dynamics, globalization, and cultural exchanges in shaping contemporary representations of lifestyle. By considering human-centric language processes, this research contributes to a deeper understanding of how linguistic practices both mirror and mold the lived experiences of individuals and groups, ultimately underscoring the inseparability of language and culture.
The city of Berehove is located in the Zakarpattia (Transcarpathia) region (Oblast) of Ukraine, near the border with Hungary. A significant part of the local population is Hungarian-speaking; that is why, for the more than 150000 Transcarpathian Hungarians, Berehove serves as an unofficial cultural center. At the time of the main data collection (2019–2021), street signs in the city could be found in Ukrainian, Hungarian, Russian, English, and other languages. Such a highly multilingual urban environment gives rise to various types of mistakes, as not all residents are fluent in the common languages. The Hungarian minority in Transcarpathia faces difficulties in learning the Ukrainian language, as it was not compulsory during the Soviet period. The compact settlement of the Hungarian population in Transcarpathia means that they may have very limited contact with speakers of Slavic languages. In addition, the grammar of Ukrainian and Russian is difficult for Hungarians. The article focuses on errors in Ukrainian and Russian texts, but also provides some examples of street signs in Hungarian and English that deviate from linguistic norms. This study proposes an approach that involves students in the joint identification and analysis of such errors in street signs. The inclusion of such exercises in the educational process can help children develop the habit of carefully observing their linguistic environment and critically evaluating their own speech.
This paper introduces new models designed to improve the morpho-syntactic parsing of the five largest Latin treebanks in the Universal Dependencies (UD) framework. First, using two state-of-the-art parsers, Trankit and Stanza, along with our custom UD tagger, we train new models on the five treebanks both individually and by combining them into novel merged datasets. We also test the models on the CIRCSE test set. In an additional experiment, we evaluate whether this set can be accurately tagged using the novel LASLA corpus (https://github.com/CIRCSE/LASLA). Second, we aim to improve the results by combining the predictions of different models through an atomic morphological feature voting system. The results of our two main experiments demonstrate significant improvements, particularly for the smaller treebanks, with LAS scores increasing by 16.10 and 11.85%-points for UDante and Perseus, respectively (Gamba and Zeman, 2023a). Additionally, the voting system for morphological features (FEATS) brings improvements, especially for the smaller Latin treebanks: Perseus 3.15% and CIRCSE 2.47%-points. Tagging the CIRCSE set with our custom model using the LASLA model improves POS 6.71 and FEATS 11.04%-points respectively, compared to our best-performing UD PROIEL model. Our results show that larger datasets and ensemble predictions can significantly improve performance.
This Capstone examines how generative AI reshapes the act of writing by treating co-writing itself as a site of inquiry. Using an autoethnographic method, I document my collaboration with ChatGPT across months of drafting, tracing how the model’s predictions influence tone, syntax, and rhetorical choice. The project argues that large language models are not neutral tools but participants in a shared writing process shaped by the linguistic hierarchies embedded in their training data. Through examples of prompting, revision, and negotiation, I show how AI leans toward standardized English, simplifies sentence structure, and reproduces dominant linguistic norms, often in ways that feel fluent but unexamined. Drawing on scholarship from linguistics, rhetoric, AI ethics, and corpus studies, I situate these patterns within broader cultural and technological shifts that are redefining authorship and literacy. My findings suggest that the future of writing will be a form of co-authorship and that ethical engagement requires vigilance, not avoidance: understanding how the model learns, questioning its outputs, and preserving human intention as the final authority. This project therefore offers both a critique of AI’s biases and a practical framework for collaborating with language models responsibly as they become embedded in the work of writing itself.
In this 2-session functional MRI study, we investigated the neurocognitive mechanisms of counterconditioning (CC). We observed ventromedial prefrontal cortex (vmPFC) activation during regular extinction, but vmPFC deactivation and nucleus accumbens activation during CC (MRI). Physiological threat responses returned in the regular extinction but not the CC group (Pupil). Furthermore, threat-associated memories from the learning and CC phase were enhanced (Behavior). This collection contains the raw, pseudonomized data of all tasks. Processed data, the SPSS mask to replicate all but the fMRI analyses (Analyses.sav), and scripts to replicate the publication figures are available at https://osf.io/mvsq6. For all tasks, fMRI, skin conductance (SCR) and pupil dilation (Pupil) data are available. For the item memory test, behavioral data (Behavior) are available. In addition, valence and arousal rating data using self-assessment manikin scales are available.
This randomized controlled study at University of Graz examines the impact of regular practice of an individual self-regulation training on psychophysiological well-being. Participants are randomly assigned to either intervention or control group. Individual self-regulation training is based on a self-regulation method used in NeuroDeescalation®. It combines elements of body movement or touch, breathing and self- encouragement. Participants in the intervention group get videos which support the acquisition of the individual self-regulation training, which should be practiced three times a day over a period of two weeks. In both groups HRV independent of metabolic demands (lmdHRV) is assessed the successive three days before and after intervention period. Furthermore, psychological variables are measured using items of the Positive and Negative Affect Schedule (PANAS), and the Mindful Attention Awareness Scale – State (MAAS – State). We expect that regular practice of an individual self-regulation training leads to higher increases in HRV independent of metabolic demands (lmdHRV), as well as higher increases in positive affect ratings, lower increases in negative affect ratings, and higher increases in state mindfulness from pre- to post- intervention compared to the control group. Statistical analyses will be conducted using mixed Analysis of Variance (ANOVA) to account for between-subjects factor (group) and within-subjects factor (measurement period).
Sanskrit is traditionally described as a free-word-order language, and the indigenous grammatical tradition explains what constrains word combination through three notions: ākāṅkṣā (syntactic expectancy), yogyatā (semantic compatibility), and sannidhi (proximity or contiguity). This study asks whether sannidhi, read as a locality constraint, is empirically supported, and how it relates to the cross-linguistic principle of dependency-length minimization (DLM). Using the Universal Dependencies Treebank of Vedic Sanskrit (27,182 sentences; 206,440 tokens), I compared observed dependency lengths against a random-projective baseline and a minimal-arrangement heuristic, partitioned arcs by grammatical relation, quantified non-projectivity, and traced variation across the corpus's chronological layers. At the whole-sentence level, Vedic showed no dependency-length minimization beyond the projectivity constraint: observed mean length (1.996) was statistically indistinguishable from the random-projective baseline (2.002) and far above the minimal arrangement (1.512). This near-parity, however, masked a systematic relation-specific split. Core verb-argument relations—the kāraka-type expectancy relations—were placed reliably closer than their own random baseline (mean deviation −0.36 tokens, 95% CI [−0.38, −0.34]), whereas coordinate, appositional, and modifier relations were placed at or beyond chance distance (+0.16 tokens, 95% CI [+0.13, +0.18]). Non-projectivity was common (19.4% of sentences) but overwhelmingly mild and well-nested, and it declined sharply from the Ṛgvedic layer (35.9%) to the Sūtra layer (11.0%). An independent classical treebank reproduced both the aggregate parity and the non-projectivity rate. I argue that sannidhi is best understood not as global length optimization but as a selective, expectancy-scoped locality operating over ākāṅkṣā-linked pairs, and that Vedic word order becomes measurably more projective over time.
Ozymandias è uno dei testi di Percy Besshy Shelley più presenti nelle antologie scolastiche inglesi. Il sonetto, per la chiarezza anche sintattica e lessicale con cui affronta il tema della vanitas vanitatum, sembrerebbe non porre particolari problemi ai traduttori. L’analisi delle traduzioni che hanno segnato la ricezione italiana di Shelley mostra come invece le scelte e le strategie traduttive abbiano ricreato testi molto diversi fra loro, coerenti con l’idea di traduzione e di poetica dominante in un certo periodo della storia del gusto e dello stile o profondamente influenzate dalla poetica del traduttore, in alcuni casi egli stesso poeta. Dopo essersi soffermato su quattro versioni pubblicate del sonetto (Carlo Faccioli 1902, Adolfo De Bosis 1928, Giuseppe Conte 1989, Francesco Rognoni 2018) e su alcune traduzioni inedite, attribuibili ad autori canonici della letteratura italiana come Leopardi e Ungaretti, il saggio si conclude con alcune considerazioni sulla traduzione letteraria e l’intelligenza artificiale. Ozymandias is one of Percy Bysshe Shelley’s most frequently anthologized texts in English school curricula. Owing to its lexical and syntactic clarity in addressing the theme of vanitas vanitatum, the sonnet would appear to pose no significant challenges for translators. Yet, this essay, by examining a range of translations that have shaped the Italian reception of Shelley, reveals how translation choices and strategies have resulted in markedly different texts. These variations often reflect the prevailing theories of translation and dominant poetic norms of a given period, or are deeply influenced by the translator’s individual poetics—who is, in some cases, a poet themselves. The essay focuses on a comparative analysis of four published versions of the sonnet (Carlo Faccioli 1902, Adolfo De Bosis 1928, Giuseppe Conte 1989, and Francesco Rognoni 2018), along with previously unpublished translations possibly attributable to canonical Italian authors such as Leopardi and Ungaretti. The essay concludes with reflections on literary translation in the age of artificial intelligence.
This thesis aims to examine the impact of mind wandering on statistical language learning, a form of implicit learning that allows the detection of patterns and regularities from external input. Mind wandering refers to the shift of attention away from an external task toward internal thoughts, often occurring involuntarily. While mind wandering is traditionally associated with impaired performance in attention-demanding tasks such as learning, emerging research suggests that mind wandering may have a beneficial effect on certain instinctual cognitive processes, such as statistical learning and implicit learning (Vékony et al., 2025). Two experiments are conducted to investigate whether mind wandering influences performance and metacognitive confidence in artificial language learning tasks. In Experiment 1, participants listen to a continuous stream of trisyllabic pseudowords and complete a two-alternative forced choice (2AFC) task, providing confidence ratings for each decision. In Experiment 2, participants complete familiarity rating tasks after exposure to both paused and continuous speech streams with either front-vowels or back-vowels. In both experiments, mind wandering is assessed through a self-report questionnaire administered after each exposure. Results indicate no significant relationship between mind wandering and statistical language learning performance. However, no participants reported fully disengaging from the tasks, which likely affected the results. Due to the limited variability in mind wandering, as indicated by the mind wandering questionnaire scores that do not indicate high mind wandering, further research is needed. Future studies should explore whether more substantial or sustained mind wandering might enhance statistical language learning, as reported in emerging research. In addition, the study design could be applied to other cognitive domains.
Abstract Data-driven Dependency Parsing approaches tend to have low accuracy for Indian languages and Nepali as compared to English and many European languages, which is due to the complex grammatical structures of these languages. Further, due to the unavailability of the universal dependency treebank, validation of any data driven Dependency Parser for the Nepali language is not possible. Therefore, we present a graph and grammar-based dependency parser for Nepali sentences. The parser works in three phases viz. Parts-Of-Speech (POS) tagging which is based on Hidden Markov Model (HMM), rule based Chunking and Dependency Parsing. The parser makes use of the maximal graph matching technique, grammatical knowledge such as verb frames, morphological information and yields the semantically and syntactically correct labeled dependency graphs (parse tree). The parser scores 80.62% on UAS (unlabeled attachment score) and 61.45% on LAS (labeled attachment score) for a random test sample of 2600 sentences.
This paper presents an approach to integrating Latin inflected forms and corpus attestations within a Linked Open Data (LOD) framework, enhancing interoperability between Wikidata and the LiLa knowledge base. Building on the PrinParLat lexicon of Latin verb principal parts, we generate the complete set of inflected forms for over 8,000 verbs, encoded as RDF in a dedicated Wikibase instance. These forms are linked to the Index Thomisticus Treebank (ITTB), whose morphologically annotated tokens are related to corresponding forms based on segmental identity, lemma alignment, and mapped morphological features. Our generation and linking process achieves over 95% coverage of ITTB verbal tokens, demonstrating the robustness of our pipeline even for Medieval Latin data. By aligning Paralex, Wikidata, and LiLa ontologies, we ensure semantic interoperability and facilitate future integration into Wikidata. Beyond Latin, this workflow provides a reproducible model for linking inflectional paradigms and corpus attestations in other languages.
This paper presents an approach to integrating Latin inflected forms and corpus attestations within a Linked Open Data (LOD) framework, enhancing interoperability between Wikidata and the LiLa knowledge base. Building on the PrinParLat lexicon of Latin verb principal parts, we generate the complete set of inflected forms for over 8,000 verbs, encoded as RDF in a dedicated Wikibase instance. These forms are linked to the Index Thomisticus Treebank (ITTB), whose morphologically annotated tokens are related to corresponding forms based on segmental identity, lemma alignment, and mapped morphological features. Our generation and linking process achieves over 95% coverage of ITTB verbal tokens, demonstrating the robustness of our pipeline even for Medieval Latin data. By aligning Paralex, Wikidata, and LiLa ontologies, we ensure semantic interoperability and facilitate future integration into Wikidata. Beyond Latin, this workflow provides a reproducible model for linking inflectional paradigms and corpus attestations in other languages.
At present, social media has developed into one of the most common communication tools used by university students. The use of social media platforms not only shapes the way individuals engage socially with one another but also leaves a significant impact on their linguistic practices, particularly in relation to the Indonesian language. The purpose of this study is to examine how social media influences students’ language habits when using Indonesian, both in written and spoken forms. A descriptive qualitative approach was employed, collecting data through observation and questionnaires administered to a group of students. The findings reveal that students who frequently use social media tend to adopt non-standard language, abbreviations, and code-mixing with foreign languages, which gradually has the potential to undermine their ability to communicate effectively and correctly in Indonesian. Nevertheless, social media also presents beneficial prospects, such as fostering greater creativity in sentence construction, expanding vocabulary, and cultivating a stronger interest in writing. Consequently, social media exerts a dual influence on students’ language behavior, encompassing both positive and negative aspects, thereby underscoring the need for awareness and the cultivation of Indonesian language use that adheres to established linguistic norms.
The article provides a concise overview of the International Scientific Conference “English Studies in the Third Millennium: New Approaches and Development Trends,” held at the Belarusian State University on October 3–5, 2024 in Minsk, Belarus. The conference brought together over 100 scholars, educators, and researchers from Belarus, Russia, and Oman, representing a wide range of academic institutions. The event, organized by the Belarusian State University, the Institute of Linguistics of the Russian Academy of Sciences, and the Moscow State Linguistic University, aimed to explore contemporary trends in theoretical and applied linguistics through the lens of interdisciplinary approaches such as cognitive linguistics, digital linguistics, intercultural communication, and multimodal studies. The conference featured plenary and sectional sessions, with presentations by leading experts in the field who discussed topics ranging from discourse analysis and linguistic narratives to the role of language in cultural identity and conflict resolution. Researchers also addressed emerging issues in English studies, such as the impact of globalization on linguistic norms, the functional dynamics of English language units, and the interconnection of language and culture. Beyond academic exchange, the conference facilitated cultural and professional networking, emphasizing the importance of interdisciplinary collaboration in addressing the challenges of modern linguistics.
As Chinese film and television productions increasingly gain international exposure, subtitle translation—an essential medium for cross-cultural communication—has attracted growing scholarly attention regarding its strategies and theoretical foundations. Chang An, a domestically produced animated film rich in cultural connotations, demonstrates a wide range of linguistic shifts in its English subtitles as it seeks to convey the original meaning and cultural essence. Grounded in Catford’s translation shift theory, this study explores subtitle translation strategies from two dimensions: level shifts and category shifts. By analyzing representative examples from the film, the paper examines the practical application of structure shifts, class shifts, unit shifts, and intra-system shifts. The findings reveal that the translator’s flexible use of various types of shifts effectively achieves semantic equivalence and facilitates the transmission of cultural information. This reflects a multifaceted consideration of linguistic norms, audience reception, and cultural adaptation in subtitle translation. Through detailed case analysis, the study aims to enrich the application of translation shift theory in subtitle translation practice and provide theoretical and practical references for future subtitle translation of Chinese animated films.
Indonesian, as both a national language and an academic language, demands clarity, precision, and adherence to syntactic, morphological, and orthographic rules. However, in practice, many student writings deviate from these linguistic norms. This study aims to identify and analyze forms of linguistic anomalies in the writings of students in the Madrasah Ibtidaiyah Teacher Education (PGMI) Program, particularly in the use of written Indonesian. This research employs a descriptive qualitative approach with content analysis techniques applied to thesis proposal documents. In addition to documentation, data were collected through direct speech observation and in-depth interviews. The subjects of this literature review consist of various written sources such as books, journals, and scientific documents. Data analysis uses content analysis to interpret information systematically and thoroughly. The results reveal that the most common anomalies include ineffective sentences, nonstandard word usage, and errors in spelling and punctuation. Contributing factors include limited academic literacy, the influence of spoken language and social media, and the lack of continuous practice in formal writing. This study highlights the importance of strengthening language learning and scientific writing training to improve the academic communication skills of PGMI students.
This article investigates the stylistic and linguistic features of Gustave Flaubert’s prose, with a particular focus on lexical contradiction and idiomatic tension. Through a close analysis of key works such as Madame Bovary, L’Éducation sentimentale, and Bouvard et Pécuchet, the study highlights how Flaubert’s writing systematically juxtaposes opposing semantic registers—romantic idealism and mundane realism, poetic elevation and trivial detail. These lexical contradictions not only enrich narrative depth but also underscore the disillusionment and irony characteristic of Flaubert’s modern vision.The article further explores how Flaubert manipulates idiomatic expressions, either by subtly distorting them or by integrating them ironically into character discourse. This tension between conventional language and authorial critique reveals Flaubert’s ambivalent relationship with linguistic norms and his pursuit of lemot juste. Drawing on French and Francophone critical literature, the study situates Flaubert’s stylistic innovation within broader debates about the literary function of cliché, the evolution of free indirect discourse, and the modern fragmentation of narrative voice.By analyzing the paradoxes at the heart of Flaubert’s style, the article demonstrates how lexical contradiction and idiomatic tension function not only as aesthetic devices but also as means of epistemological inquiry—interrogating language,meaning, and the act of writing itself.
The primary challenge in studying children's and adolescents' emotional issues lies in reliably and effectively eliciting their emotional states in research settings, a process that is essential for understanding the development and regulation of emotions across childhood and adolescence. Current research in this field predominantly employs situational induction, facial expression paradigms, and audiovisual stimuli as the main approaches to evoke emotional responses in young participants. While these methods have provided valuable insights, a critical limitation of existing pediatric emotion elicitation techniques is their adult-centric design framework, which often fails to fully account for the developmental origins, contextual factors, and age-specific characteristics of children's and adolescents' emotional experiences. In response to this limitation, the present study advocates for a child-centered research approach that explicitly prioritizes the emotional experiences of youth, aiming to enhance ecological validity by designing stimuli that are closely aligned with the everyday social and environmental contexts in which children and adolescents naturally experience emotions. Furthermore, given the current lack of culturally appropriate and developmentally tailored image databases for socio-emotional elicitation in young populations, this research seeks to construct a child-validated image library capable of safely and effectively eliciting emotional responses. The resulting database is intended to provide a reliable experimental platform that can be used to investigate the mechanisms of emotional processing in youth and to support subsequent interventions and programs aimed at promoting emotional health and socio-emotional development. Two empirical studies were conducted to establish and validate the Chinese Child-Adolescent Affective Picture System (CCAAPS). In Study 1, semi-structured interviews with children and adolescents from Shandong and Anhui provinces in China were analyzed using grounded theory to identify principal sources of emotion in daily life. A total of 20 participants, balanced by gender and aged 6–18 years, provided narratives highlighting a range of emotional triggers. Findings revealed that interpersonal interactions—particularly school-based social contexts—constituted the primary emotional triggers. These qualitative insights were systematically coded to extract keywords that guided the selection of images for the database. Study 2 recruited a total of 491 participants, aged between 6 and 18 years. Each participant was asked to evaluate a set of 311 socio-emotional images that had been preselected based on the findings from Study 1. The images were rated along three distinct emotional dimensions—valence, arousal, and motivational intensity—using a revised 5-point Likert scale. Analysis of the subjective ratings revealed statistically significant differences among positive, neutral, and negative images across all three dimensions (p <.001 for all comparisons), demonstrating that the images were capable of eliciting differential emotional responses in a manner consistent with their intended affective categories. Furthermore, the internal consistency of participants’ ratings was assessed using Cronbach’s alpha, yielding coefficients exceeding 0.85 for each dimension. These results indicate that the image ratings were reliable across participants and that the emotional dimensions measured were internally coherent. The CCAAPS has several implications. First, as a standardized tool grounded in children’s real-life experiences, it provides a link between laboratory paradigms and everyday emotional phenomena, supporting research on emotion recognition, affective processing, emotion-related psychopathology (e.g., depression, anxiety), interpersonal regulation, and antisocial behaviors such as bullying. Second, it can be applied in socio-emotional learning (SEL) to provide culturally appropriate materials for empathy training and emotion regulation interventions in educational contexts. Third, by providing a validated, developmentally appropriate, and culturally adapted affective picture system, the CCAAPS enhances methodological infrastructure for developmental affective science in China. In conclusion, the present research contributes both conceptually and practically to the study of youth emotions by constructing the first child-centered, culturally adapted affective picture system for Chinese children and adolescents. The CCAAPS establishes an ecologically valid resources for investigating socio-emotional experiences, enriches the toolkit for researchers. This work therefore provides an essential infrastructure for future studies seeking to understand, support, and promote the emotional health of Chinese youth.
The article examines the linguistic features of Gumar Karash, a prominent Kazakh intellectual, public figure, and writer of the early twentieth century. The study identifies lexical units characteristic of his works, including nouns, adjectives, pronouns, regional vocabulary, and borrowed lexicon, and analyzes their semantic and functional properties. These linguistic elements are examined in comparison with the norms of modern Kazakh literary language, Turkic written monuments, and the language of Karash’s contemporaries, which allows for a clarification of the author’s individual stylistic profile. The analysis highlights Karash’s use of borrowed words either in forms close to the original or adapted to Kazakh phonetic patterns, his incorporation of regional speech elements, his command of the classical written tradition, and his application of Turkic language structures. The aim of the study is to determine the semantic and functional characteristics of various lexical layers (nouns, adjectives, pronouns), regional words, and borrowed vocabulary in Karash’s writings, as well as to identify the author’s distinctive linguistic and stylistic features. The research demonstrates the preservation of archaic usages, the frequency of dialectal elements, variation in the phonetic representation of Arabic-Persian borrowings, and Karash’s productive word-formation based on the internal resources of the Kazakh language. The findings show the poet’s contribution to the development of the Kazakh literary language in the early twentieth century and justify the historical motivation of his linguistic choices.
The article is devoted to various aspects of the culture of the post-revolutionary period. The authors analyze the significant transformations that occurred in the cultural tradition of that time and examine the facets of human life that were fundamentally shaped by the new culture of the post-revolutionary period. The relevance of this study is due to the importance of cultural policy in modern Russia. In this regard, the experiences of cultural construction during the early years of Soviet power hold considerable significance and merit thorough exami-nation. The scientific novelty of this research lies in the fact that, for the first time, the authors trace the connec-tion between the cultural policy of the Bolsheviks and the linguistic norms that emerged during the post-revolutionary period. Furthermore, they analyze the interrelation of language, culture, and the political events of that time. The authors identify the causes and origins of the formation of cultural policy while considering its essential features. They investigate its impact on the society of the historical period in question, as well as on the lifestyles of the broadest masses of the populace. In this regard, the authors scrutinize how the introduction of a new system of values and social orientations led to the dismantling of prior cultural traditions and the es-tablishment of new ones. This transformation was particularly evident in public consciousness and the linguistic sphere of societal existence.
Code-switching presents a complex challenge for syntactic analysis, especially in low-resource language settings where annotated data is scarce. While recent work has explored the use of large language models (LLMs) for sequence-level tagging, few approaches systematically investigate how well these models capture syntactic structure in code-switched contexts. Moreover, existing parsers trained on monolingual treebanks often fail to generalize to multilingual and mixed-language input. To address this gap, we introduce the BiLingua Parser, an LLM-based annotation pipeline designed to produce Universal Dependencies (UD) annotations for code-switched text. First, we develop a prompt-based framework for Spanish-English and Spanish-Guaraní data, combining few-shot LLM prompting with expert review. Second, we release two annotated datasets, including the first Spanish-Guaraní UD-parsed corpus. Third, we conduct a detailed syntactic analysis of switch points across language pairs and communicative contexts. Experimental results show that BiLingua Parser achieves up to 95.29% LAS after expert revision, significantly outperforming prior baselines and multilingual parsers. These results show that LLMs, when carefully guided, can serve as practical tools for bootstrapping syntactic resources in under-resourced, code-switched environments. Data and source code are available at https://github.com/N3mika/ParsingProject
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The present dissertation examines the role of context-specific simulations in influencing the complexity of affective experiences, drawing on a constructivist approach to emotion. To link literatures on mental simulation and emotion, in Chapter 1 a connection is made through the grounded theories of cognition. Chapter 2 describes the development of a novel dataset consisting of context-dependent stimuli (i.e., 1,381 picture-word cues derived from 320 pictures-only stimuli) validated through online experiments (NExp1= 1,934; NExp2 = 403). Hence, an investigation of how contextual information influences the affective experience is illustrated, revealing that context more often enhances affective complexity by widening, rather than narrowing, the variation in the between-subject valence ratings. Chapter 3 employs a set of stimuli selected from Chapter 2 in a lab-based experiment in which participants (N = 30) rated affect intensity, and reported which emotions and bodily sensations experienced in response to generating both mental images and verbal thoughts. Mental imagery was found to enhance emotion complexity as reflected in the richness of the reports provided, with affect intensity and autobiographical recall accounting for the effect. Finally, in Chapter 4 the influence of mental imagery on emotion complexity will be studied across the imagery spectrum. To this end, in an online experiment participants (N = 72) completed measures of imagery vividness, alexithymia and gave written reports on how they feel when experiencing emotions at varying levels of valence and arousal, to obtain indexes on the complexity of emotion conceptualization. In line with the predominant literature, the more vivid the visual mental imagery of participants, the less alexithymia was reported, i.e., the less impaired is the process of emotion conceptualization. As highlighted in the final chapter (Chapter 5), overall the present dissertation contributes to deepening the study of the relationship between mental imagery and emotion. Assuming variation as inherent to emotion, consistently through different experimental designs, methods, languages and indexes, it is shown how context-specific simulations enrich the emotional sphere, by enhancing the complexity of affective experiences.
V prispevku je predstavljen postopek izdelave korpusa CVET, ki vsebuje besedila patra Hijacinta Repiča, objavljena v verski reviji Cvetje z vertov sv. Frančiška v obdobju 1881–1916. Korpus je uporabljen kot podlaga za jezikovno in stilistično analizo, opravljeno z orodjem noSketch Engine. Z analizo frekvenčnosti izbranih spremenljivk sta opisana besedišče patra Repiča in njegov pripovedni slog. Nazadnje je na primeru besed tipa bralec/bravec opazovan sinhrono-diahroni in normativni vidik starejšega slovenskega jezika besedil v korpusu.
The digital era has brought profound changes to language, particularly visible in the rapid emergence of new lexical units. This article explores how internet communication, social media, and technological innovations influence language change, leading to the creation and diffusion of novel words and expressions. By analyzing examples from contemporary digital discourse, the study highlights the dynamic nature of language and the impact of digital culture on vocabulary expansion. The article also discusses the implications of these changes for language norms and linguistic identity.
International audience
We present EmoWork, a multimodal, multi-label dataset designed to support emotion and stress detection in realistic interpersonal work settings. Interpersonal work—common in occupations such as customer service—often requires workers to regulate their emotional expressions in response to strong affective stimuli. These demands, shaped by organizational display rules, present a unique challenge for affective computing systems, particularly in scenarios where internal emotional states diverge from observable behaviors.Despite this, no public datasets exist that capture such dynamics of affect in naturalistic settings. To address this gap, we collected physiological, behavioral, and self-reported data from call center workers who engaged in role-play scenarios simulating customer service interactions with professional actors portraying dissatisfied customers. The dataset includes self-reported affective ratings, which are used as labels for classification, synchronized recordings from three wearable devices (i.e., Polar H10, Empatica E4, and Muse S), and features extracted from video and audio data. The EmoWork dataset advances affective computing by offering context-rich, multimodal data grounded in realistic interpersonal work scenarios.
Large language models (LLM) perform outstandingly in various downstream tasks.However, there is limited understanding regarding how these models internalize linguistic knowledge, so various linguistic benchmarks have recently been proposed to facilitate syntactic evaluation of language models (LM) across languages.This paper introduces QFrCoLA (Quebec-French Corpus of Linguistic Acceptability Judgments), a normative binary acceptability judgments dataset comprising 25,153 in-domain and 2,675 out-of-domain sentences.Our study leverages the QFrCoLA dataset and seven other linguistic binary acceptability judgments corpus to benchmark eight LM.The results demonstrate that, on average, finetuned Transformer-based LM are strong baselines for most languages and that zero-shot binary classification LLM perform worse than the naive baseline on the task.However, for the QFrCoLA benchmark, on average, a finetuned Transformer-based LM outperformed other methods tested.It also shows that pretrained cross-lingual LLMs selected for our experimentation do not seem to have acquired linguistic judgment capabilities during their pre-training for Quebec French.Finally, our experiment results on QFrCoLA show that our dataset, built from examples that illustrate linguistic norms rather than speakers' feelings, is similar to linguistic acceptability judgment; it is a challenging dataset that can benchmark LM on their linguistic judgment capabilities.
This study is concerned with the English neologisms of Generation Z Language users (popularly called Gen-Z), whose linguistic norm is gaining entry into the English language used in social media, thus influencing the language of four generations which are categorised based on birth years and shared cultural experiences. The four generations include Generation X, Millennials, Generation Z and Generation Alpha, and these categories of people form a set of active users of English Language, especially on social media. This language norm makes a remarkable impression on the vocabulary of English with the existence of social media since there is often an explosion in the frequency with which speakers make use of such innovation or construction in the target language. What is unique about the neologisms of the Generation Z English users is first, the pace with which they are formed and used and second, the ease with which they gain traction among diverse users. Although this speed is an unusual feature of language change which its process is measured, it is imperative to note that language innovation is ceaseless and remorseless. Every language that is spoken continues to change, not just century by century, but day by day. The aim of this study is to examine the neologisms formed by Generation Z users of English and establish the morphosemantic features peculiar to the formation of those words. The objectives are to i. identify Gen-Z neologisms, ii. analyse the possible sources and morphological processes used in the formation, and iii. ascertain the relationship between the new words and the corresponding old words (if any). In this study, some of the neologisms formulated in the last 15 years were accessed, the sources and origins of the words were investigated and finally the morphological processes used to achieve the words and their attendant meanings as well were examined. This study acknowledges the existence of Generation Z who exhibit unique characteristics that distinguish them from other past generations. Their distinctiveness is a product of their childhood and life in the technological, culturally diverse, digitally connected and socially conscious world. Being the core of the active population in this age, they influence various aspects of the society from technology and media to business, fashion and learning which indeed cause fundamental changes in the present world and initiate future directions. The evident rapid and profound changes in the English lexis in the last few decades require systematic linguistic investigation.
Este é um estudo em andamento sobre Processamento de Língua Natural de um corpus de Narrativas Clínicas em português brasileiro com duas versões anotadas: uma pela máquina e outra por humanos. A frequência dos rótulos das classes de palavras e das relações de dependência dos tokens em cada versão é calculada e uma análise guiada pelo corpus é realizada, destacando as correções feitas pelos humanos nas anotações da máquina. A comparação dessas anotações permite a criação de treebanks que podem ser usados para treinar novos modelos usando técnicas de aprendizado de máquina e para aprimorar diversas aplicações de Processamento de Língua Natural com corpus da área biomédica. Além disso, essa comparação permite a análise da consistência teórica de anotação, a fim de identificar o sistema gramatical desse tipo de corpus e criar guias de anotação para Narrativas Clínicas em português brasileiro de acordo com as Dependências Universais.
Factors that predict second language (L2) collocation knowledge have been extensively studied, but research on predictors of L2 knowledge of idioms is still limited. The aim of the present study is to examine the effect of various factors established in L2 collocation research on idioms. These include L2 proficiency, idiom frequency, and congruency status (whether the idiom can be literally translated into the first language or L1). To that end, 225 L1-Arabic–L2-English speakers completed three measures (familiarity rating, meaningfulness rating, and meaning recall) involving 72 English idioms, half congruent and half incongruent. Additionally, the participants completed a vocabulary size test as a rough measure of their English proficiency. We initially examined the association between the ratings provided by the L2 participants and those of L1 speakers, which are available through a norming study. Then, we fit mixed-effects models to examine predictors of the three outcome measures. Raw meaning recall scores indicated that only 33% of the target idioms had their meanings correctly recalled. The statistical analysis showed a strong positive interaction between the familiarity and meaningfulness ratings provided by L2 speakers. However, the association between L1 and L2 ratings was weaker. Results of mixed-effect modelling showed that for all three measures, only estimated proficiency and congruency were significant determinants of L2 idiomatic knowledge. Additionally, estimated proficiency modulated the congruency effect only for the rating measures, with a larger difference between congruent and incongruent idioms as proficiency increased. We discuss the implications of these findings to the teaching and learning of L2 idioms.
The article analyzes the key theoretical and practical aspects of developing lexical competence in the process of learning Ukrainian as a foreign language. Lexical competence is considered an essential component of foreign language communicative competence, ensuring effective communication in accordance with linguistic and cultural norms. The author explores the peculiarities of vocabulary acquisition at the initial (A1), basic (A2), and threshold (B1) levels of Ukrainian language proficiency. The study examines teaching methods that include systemic-linguistic, conditional-communicative, and communicative types of exercises, as well as interactive methods such as language games, working with texts, and visual learning aids. Through the communicative approach, which involves working with realistic texts, role-playing games, and situational dialogues, the process of immersing foreign learners in the language environment is implemented. Based on the topic “Professions,” both traditional systemic-linguistic and communicative tasks adapted to the needs of foreign learners are proposed. The presented set of exercises is aimed at the gradual development of lexical skills, ranging from familiarization with new words to their active use in speech. It facilitates the development of reading, speaking, listening, and writing skills. These tasks help foreign learners work with texts and create their own. The use of such methods contributes to increasing students’ motivation and enhancing the effectiveness of vocabulary acquisition. Reading or listening to texts about famous Ukrainians fosters linguistic and cultural competence. The described approaches can be applied both in classroom settings and for independent student work. The practical significance of this study lies in the introduction of modern approaches to teaching Ukrainian vocabulary as a foreign language. The proposed approaches and types of exercises can be adapted for studying other topics in a foreign language audience at all proficiency levels. Key words: methods of teaching Ukrainian as a foreign language, lexical competence, language proficiency levels, exercises.
Horses are depended on as work animals by humans and are used in leisure and sport across the world, but the extent to which humans can recognise pain in horse faces is not known, which could impact their welfare. There are also significant gaps in our understanding of which psychological traits influence recognition of human facial expressions of pain. To address this, one hundred participants, with either some (N = 30) or no prior horse care experience (N = 70), rated thirty human and thirty horse faces for pain, arousal and valence and completed trait measures of empathy and social anxiety. Ten equine behaviour professionals also rated the horse faces as a baseline for assessing accuracy. Overall, accuracy of pain recognition was higher for human faces, but participants with horse experience were more accurate at pain recognition in horse faces, than those without, and years of horse experience predicted horse pain recognition accuracy. Social anxiety traits predicted accuracy of pain recognition in human but not horse faces, while also predicting subjective ratings of pain in horse but not human faces. Empathy and its cognitive and emotional components were not related to pain recognition accuracy or ratings of horse or human faces. Relationships between trait measures and arousal and valence ratings for both species are reported. This study is the first to report the human ability to read pain in horse faces and the factors which influence this and extends current knowledge on face processing in social anxiety.
The article presents the results of a cross-cultural affective images perception study by Americans and Russians and reveals the degree of cultural factor influence on the stimuli assessment by American and Russian men and women. The hypothesis is that assessments of affective images by American and Russian respondents will have statistical differences due to the linguistic and cultural specificity of the ethnic groups; it is also assumed there are cross-cultural gender differences in the assessment. The study used the method of psycholinguistic questioning with seven-point scaling. 84 images from the open American database of affective images (“Open Affective Standardized Image Set”) were used as research material. The respondents were 34 men and 58 women. The results of the analysis did not show significant cross-cultural differences in ratings of affective images with reference to valence type or emotional evaluation/response. In general, Americans and Russians had a similar distribution of image ratings. However, a statistically significant difference has been found in the ratings of images with different valence types (P < 0.001). Negative and positive images were rated higher by Russians in terms of emotional evaluation, in contrast to Americans, most of whose emotional responses had neutral ratings. There was also a statistically significant difference in the ratings of different thematic images (P < 0.05). Nature images were rated by Russians as causing a feeling of comfort, while Americans noted their neutral impact on them. Images of objects, on the contrary, received the opposite ratings from the respondents. Moreover, cross-cultural gender differences have been revealed between Russian and American women in image ratings based on emotional evaluation and valence parameters (P < 0.05). Russian women rated most of the images as having a positive or negative impact, while the majority of American women’s ratings tended to be neutral. This confirms the influence of the emotional stimulus, valence type, image theme, as well as gender factor on the processing of emotionally coloured units by representatives of different cultures.
This research introduces a framework for comparative evaluation of human-curated versus AI-generated affective images using a multimodal AI agent. The dataset (N=80 pictures) includes a selection of 40 human-curated images from the Open Affective Standardized Image Set (OASIS), and a set of 40 synthetic images generated specifically for this study. The synthetic dataset was created by prompting the “GPT Image 1” model, a specialized image generation model built on GPT-4o, with the goal to represent four target emotional states—Excitement, Frustration, Boredom, and Relaxation. A custom AI agent was deployed to rate all images along the valence and arousal dimensions of the affective circumplex model. Statistical analyses were performed to compare: (1) human vs agent image ratings for OASIS and (2) the agent’s ratings of the AI-generated image set and OASIS. The findings indicate that the AI agent reliably aligned with the human ratings and that GPT-4o can serve as both a generator and evaluator of affective content, thus supporting scalable, human-free validation pipelines. This approach contributes to the field of affective computing by enabling rapid generation and analysis of emotionevoking stimuli, with potential applications in experimental psychology and mental health.
The galvanic skin response (GSR) has provided important scientific insight in a wide range of contexts and has been used in neuroscience research for many decades. It is important for undergraduate students to understand this versatile technique and its application in areas such as Affective, Behavioral, and Forensic Neuroscience. Participants in this study viewed a slideshow containing negative and neutral images selected from the RADIATE and IAPS databases after being connected to a small portable GSR biofeedback monitor. Images were presented for 7-sec on a computer screen followed by a 20-sec blank screen. Each participant's highest GSR response during the 7-sec image presentation was recorded. Participants provided a valence rating, using a 5-point Likert scale, immediately after each image was presented. The mean GSR for images rated as negative was significantly higher than the mean GSR for images rated as neutral. Results were discussed with the class prior to the completion of demographic and activity effectiveness questionnaires. All responses were significant on the activity effectiveness questionnaire. Participants reported a better understanding of the use of GSR in neuroscience, considered this activity a valuable experience, and recommended its use in future classes.
BACKGROUND: Emerging research suggests that behavioral-variant frontotemporal dementia (bvFTD) involves distinct deficits in processing social concepts -units that denote interpersonal traits, events, and circumstances. Recent findings indicate that assessments of these domains could contribute to differential diagnosis and predict syndrome-specific neural alterations. However, unlike other semantic categories, social concepts lack normative datasets for under-represented languages, which hinders strategic stimulus selection for much-needed experiments on under-served populations. To tackle this gap, we created a normative psycholinguistic database of social and non-social concepts for Spanish-speaking Latinos, aimed to fuel groundbreaking research on this population. METHODS: Healthy subjects over 18 years old completed an online form, rating 600 Spanish words (nouns, verbs, adjectives) in terms of their meanings' social relevance. Subsets of 100 words with high and low sociality (e.g., "friendship" and "button", respectively) were randomly presented. After rating their comprehension of the instructions, participants assessed the sociality of each word using a Likert scale (1 = no sociality, 7 = high sociality). Stimuli selection was made based on Diveica et al. (Behav Res Methods 2023, 54:461-73), who achieved strong validity in categorizing social and non-social English words, and socialness-driven variance in lexical tasks. Participants were recruited through flyers in online educational platforms and social media. RESULT: Socialness ratings averaged 5.997 (SD = 0.873) for social words and 1.75 (SD = 0.909) for non-social words. Participants provided more consistent responses at the extremes of the scale. These findings suggest strong face validity and a clear distinction between categories. CONCLUSIONS: Focusing on linguistic tools, we aim for a comprehensive study of social concepts and their potential as markers of cerebral dysfunction. In particular, we hope to enhance clinical investigation and diagnoses for populations with bvFTD, while fostering a fertile ground for novel translational research. This Spanish database is crucial for data collection in underrepresented populations and contributes to equity in dementia research and, more broadly, in behavioral neurology, by incorporating the Latin American perspective.
Abstract Memory for emotional information is greater than for non-emotional information and is enhanced by sleep-related consolidation. Previous studies have focused on emotional arousal and valence of established stimuli, but what is the effect of sleep on newly acquired emotional information? Figurative expressions, which are pervasive in everyday communication, are often rated as higher in emotionality than their literal counterparts, but the effect of emotionality on the learning of metaphors, and the effect of sleep on newly acquired emotionally negative, positive and neutral language, is as yet poorly understood. In this study, participants were asked to memorise conventional (e.g. ‘ sunny disposition’ ) and novel (e.g. ‘ cloudy disposition’ ) metaphorical word pairs varying in valence, accompanied by their definitions. After a 12-hour period of sleep or wake, participants were tested on their recognition of word pairs and recall of definitions. We found higher arousal ratings were related to increased recognition and recall performance. Furthermore, sleep increased the accurate recognition of all word pairs compared to wake but also reduced the valence of word pairs. The results indicate better memory for newly acquired emotional stimuli, a benefit of sleep for memory, but also a reduction in emotional arousal as a consequence of sleep consolidation.
Theories of language and conceptual development have proposed that social relevance is helpful for understanding and acquiring the meanings of abstract words. However, there have been few direct tests of these relationships. In the present study we used a newly quantified measure of word socialness, alongside word concreteness and valence ratings, to determine if children acquire more social abstract words earlier than less social abstract words. Our analysis included 4,047 words and examined the relationships among word socialness, valence, concreteness and frequency in relation to age of acquisition ratings and, separately, test-based age of acquisition. We found that socialness significantly predicted age of acquisition, facilitating learning of abstract words more than concrete words. However, this greater benefit to abstract words was diminished when accounting for emotional valence. Furthermore, there was a significant interaction between socialness and valence which suggests there may be subsets of highly social and emotional words that are earlier acquired, regardless of concreteness. Our findings highlight the importance of socialness in word learning and underscore the necessity for a more nuanced examination of social concept subtypes to fully understand its facilitatory role in abstract word acquisition.
The expansion and consolidation of the use of state language in scientific and professional domains is one of the priority directions of Kazakhstan’s language policy and national development strategy. In this regard, the adaptation of sectoral terminology, including the medical terminological system, to national linguistic norms is particularly relevant in the process of enhancing the status of the Kazakh language as a language of science. The study of the terminological nature of bone and joint names allows for the identification, structuring and systematization of the fundamental lexical layer of national medical terminology. As a structural core of anatomical terminology, bone and joint names form the basis of medical diagnoses, disease nomenclature, and clinical discourse. Their unification, codification and lexicographical description in the Kazakh language are considered essential steps toward ensuring the full-fledged functioning of the state language in medical education, professional translation and the healthcare system. Despite belonging to the original lexical fund of the Kazakh language and being widely used in ethnolinguistic and phraseological domains, their representation in modern sectoral dictionaries, textbooks and especially in clinical discourse remains inconsistent. The lexical field of bones and joints, shaped by traditional medicine and embedded in the national worldview and value system of the Kazakh people, has a rich historical, linguistic, and cultural foundation. Considering these lexical units as an integral part of the national terminological system constitutes an important scientific and applied task. This article examines the linguistic foundations of the Kazakhization process in the medical terminological system. It substantiates the relevance of studying bone and joint terminology, analyzing the degree of their codification in the Kazakh language, models of term formation, and the current state of their lexicographical representation.