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 examines the key challenges and development directions of modern linguistics. Focus is placed on the processes of digital language transformation, the influence of the internet on linguistic norms, and the cognitive and sociolinguistic aspects of communication. The author emphasizes the need for an interdisciplinary approach to the study of linguistic phenomena in the global information space.
While the linguistic shifts between Ottoman and modern Turkish are well-documented qualitatively, quantitative analyses remain scarce.This study addresses this by conducting a comparative computational analysis using two Universal Dependencies treebanks: OTA-DUDU for Ottoman Turkish and TR-BOUN for modern Turkish.By employing descriptive statistics and a log-likelihood ratio test, we demonstrate the change and quantify the magnitude of diachronic variation.The analysis yields three primary statistical findings.First, our data reveals a 77% compliance rate with labial vowel harmony for suffixes, while this value is 98% in modern Turkish.This discrepancy can be explained by the presence of rounding in Ottoman Turkish, which disappears in modern Turkish.On the other hand, the compliance rate of palatal vowel harmony is quite high for both languages, 96% for Ottoman Turkish and 99% for modern Turkish.Second, some suffixes, such as the converb -(y)Ip 1 and the dative infinitive -mAyA, changed by reducing their allomorphs in modern Turkish.Third, we demonstrate that Arabic and Persian pluralization rules, which constituted 28% of plural nouns in Ottoman Turkish, lost their pluralizing function in modern Turkish, although the words remain with singular meaning.
Using semantic dependency analysis, this study examines narrative productions from Mandarin-speaking preschool children aged three to six to investigate how semantic organization develops with age in early childhood. Four semantic dependency treebanks were constructed from a Chinese narrative corpus available in the CHILDES database. By comparing semantic dependency types and semantic dependency distances across the four age groups, we found that (1) semantic organization shifted from experiencer and classification relations toward agent and patient relations, situational-role relations (particularly those involving measurement, individuation, and direction), and structural relations; (2) mean semantic dependency distance (MSDD) increased with age, as adjacent dependencies decreased and longer dependencies became more frequent. This increase in MSDD indicates growing complexity in semantic organization and is largely driven by significant increases in the MSDD values of specific semantic dependency types. These findings provide new evidence for semantic organization development in preschool children.
Thermal imaging, which is contact-free, light-independent, and effective in detecting skin temperature changes that reflect autonomic nervous system activity, is expected to be useful for emotion sensing. A recent thermography study demonstrated a linear relationship between ear temperatures and emotional arousal ratings. However, whether and how ear thermal changes may be nonlinearly related to subjective emotions remains untested. To address this issue, we reanalyzed a dataset that included ear thermal images and self-reported arousal ratings obtained while participants watched emotion-eliciting films. We employed linear regression and two nonlinear machine learning models: a random forest model and a ResNet-50 convolutional neural network. Model evaluation using mean squared error and correlation coefficients between actual arousal ratings and model predictions indicated that both machine learning models outperformed linear regression and that the ResNet-50 model outperformed the random forest model. Interpretation of the ResNet-50 model using Gradient-weighted Class Activation Mapping and Shapley additive explanation methods revealed nonlinear associations between temperature changes in specific ear regions and subjective arousal ratings. These findings imply that ear thermal imaging combined with machine learning, particularly deep learning, holds promise for emotion sensing.
This paper presents a novel treebank-driven approach to comparing syntactic structures in speech and writing using dependency-parsed corpora. Adopting a fully inductive, bottom-up method, we define syntactic structures as delexicalized dependency (sub)trees and extract them from spoken and written Universal Dependencies (UD) treebanks in two syntactically distinct languages, English and Slovenian. For each corpus, we analyze the size, diversity, and distribution of syntactic inventories, their overlap across modalities, and the structures most characteristic of speech. Results show that, across both languages, spoken corpora contain fewer and less diverse syntactic structures than their written counterparts, with consistent cross-linguistic preferences for certain structural types across modalities. Strikingly, the overlap between spoken and written syntactic inventories is very limited: most structures attested in speech do not occur in writing, pointing to modality-specific preferences in syntactic organization that reflect the distinct demands of real-time interaction and elaborated writing. This contrast is further supported by a keyness analysis of the most frequent speech-specific structures, which highlights patterns associated with interactivity, context-grounding, and economy of expression. We argue that this scalable, language-independent framework offers a useful general method for systematically studying syntactic variation across corpora, laying the groundwork for more comprehensive data-driven theories of grammar in use.
Background: Emotion processing is critical in the neuropathology of major depressive disorder (MDD), while its relationship with clinical treatment remains unclear. This study aims to indicate the associations between emotion processing and treatment effects following a sequential dual-site accelerated repetitive transcranial magnetic stimulation (rTMS) protocol. Methods: MDD patients were recruited to receive rTMS treatment with four sessions per day for four consecutive days, with stimulation sequentially delivered to the left dorsolateral prefrontal cortex (dlPFC) and the dorsomedial prefrontal cortex (dmPFC). Symptoms were assessed at baseline, end of treatment, and week 4 using the Montgomery–Åsberg Depression Rating Scale (MADRS), Snaith-Hamilton Pleasure Scale (SHAPS), and Fatigue Severity Scale (FSS). Emotional valence and arousal were evaluated with the Affect Rating Task (ART). Results: A total of 51 participants completed the clinical assessments and ART, with two excluded due to missing baseline data in the SHAPS and FSS. The linear mixed-effects models revealed significant improvement in depressive (p < 0.001, d = −0.343) and fatigue symptoms (p = 0.010, d = −0.572) following rTMS treatment. Neutral valence was correlated with MADRS scores at baseline (R2 = 0.096, p = 0.027). In addition, changes in arousal for positive images (p = 0.047, adjusted R2 = 0.097) and neutral images (p = 0.019, adjusted R2 = 0.160) at treatment end were significantly correlated with MADRS improvement at week 4. Conclusions: Our study highlights the association between changes in emotional arousal and improvement in MDD following accelerated dlPFC-dmPFC dual-site rTMS treatment.
Code-mixed text from social media poses significant challenges for syntactic analysis due to irregular grammar, non-standard usage, and frequent language switching. For Telugu-English code-mixed text, the absence of large-scale syntactic resources and specialized parsing models limits progress in downstream multilingual NLP applications. In this work, we address this gap by introducing the first substantial manually annotated Telugu-English code-mixed dependency treebank of 4,152 sentences, developed using Universal Dependencies (UD) 2.0 guidelines. We further propose enhancements to a biaffine dependency parser by incorporating a language-aware head-dependent bias and relation-specific structural weights to better capture cross-lingual syntactic patterns. Our approach improves parsing performance, achieving 75.53% UAS and 61.86% LAS, with consistent gains over a strong baseline. In addition, we demonstrate that integrating dependency-derived syntactic features into a BiLSTM-CRF model improves part-of-speech tagging, achieving a macro-F1 score of 83.73%, with statistically validated gains. We also re-annotate an existing Telugu-English dataset using UD 2.0 to ensure compatibility with modern syntactic frameworks. Overall, this work provides new annotated resources and modeling strategies that advance syntactic processing for Telugu-English code-mixed text, with broader implications for developing robust NLP systems in low-resource and multilingual settings.
This article evaluates the integration of data extracted from a French syntactic lexicon, the Lexicon-Grammar (Gross, 1994), into a probabilistic parser. We show that by applying clustering methods on verbs of the French Treebank (Abeillé et al., 2003), we obtain accurate performances on French with a parser based on a Probabilistic Context-Free Grammar (Petrov et al., 2006).
Abstract Native‐speaker norms continue to dominate English language education, reinforcing hierarchies that marginalize diverse Englishes and sustain linguistic injustice in contexts like Thailand. This qualitative study examines the impact of Global Englishes (GE)‐oriented pedagogy on undergraduate students' engagement with linguistic norms, identity, and structural inequality. Data were drawn from semi‐structured interviews and reflective journals with 21 students across seven Thai universities and analyzed using inductive qualitative content analysis. Findings indicate four interrelated areas of transformation. First, students showed early signs of ideological reorientation toward linguistic equality, challenging internalized native‐speaker norms and affirming English as a shared, pluricentric resource. Second, participants reported sociolinguistic empowerment, articulating increased confidence in localized English use and rejecting deficit‐based framings of accent and grammar. Third, students began to develop critical awareness of linguistic inequality, identifying how language standards function as gatekeeping mechanisms that intersect with racial and geopolitical hierarchies. Finally, they offered pedagogical and curricular critiques, exposing the exclusionary logic of monolingual norms and advocating for more inclusive materials and assessment practices, while also acknowledging institutional resistance to change. GE‐informed pedagogy shows potential to unsettle dominant language ideologies, yet its impact is constrained by institutional adherence to native‐speaker norms. Addressing these constraints requires systemic reform in English language teaching curriculum, assessment, and teacher education.
Facial expressions are powerful signals of human emotion, shaping both human–human and human–computer interaction. As interactive technologies, from adaptive interfaces to emotion-aware agents, become more pervasive, systems are increasingly expected to recognize and respond to users’ emotions naturally. But what if a system misreads your face? Such misinterpretation is particularly likely when cultural differences in emotion perception are overlooked. This problem may be compounded by the fact that most facial emotion recognition (FER) models are trained on datasets that reflect the norms of a particular cultural group that assume universality, limiting their reliability in multicultural contexts. Surprise, in particular, is an emotion whose valence can be either positive or negative depending on context, making it a critical case for investigating cultural bias in FER. To address this, we examined how cultural background shapes the recognition and valence interpretation of surprise facial expressions among South Korean (N=36) and American (N=34) participants. Participants labeled 200 facial expressions (surprise and fear), rated their perceived valence, and described personal experiences of surprise. Results show that South Korean-labeled surprise expressions exhibited stronger negative Action Unit (AU) activation and lower valence ratings, whereas American-labeled ones showed more balanced or positive facial cues. Qualitative accounts further revealed that South Koreans framed surprise as tense or socially cautious, while Americans viewed it as open and situationally flexible. These findings bridge recognition and interpretation in cross-cultural emotion research and highlight the need for culturally adaptive FER systems that can interpret ambiguous emotions like surprise more inclusively.
Abstract Arousal and valence are fundamental dimensions of affective experience signifying levels of activation and pleasantness, respectively. These dimensions play a crucial role in shaping emotional responses and behaviors, with significant implications for psychopathology. Previous machine learning studies had some success decoding these states from brain activation patterns observed during task-based functional magnetic resonance imaging (fMRI), but the results have varied across studies. Moreover, prior studies have often been limited by small sample sizes, weak decoding performance, and non-whole-brain analyses, leaving the neural representations of arousal and valence largely unresolved. Here we successfully decoded arousal and valence from whole-brain task-fMRI data collected from 132 participants during exposure to 300 unique emotional stimuli, including 150 movie clips and 150 text scenarios that reliably induced a wide range of arousal and valence states. Mass univariate general linear models identified block-level activation (emotion stimuli > washout) from all gray matter voxels. Multivariate regression analysis predicted arousal and valence ratings based on these gray matter activations. Patterns in the fMRI data underlying arousal and valence were robust, as they were successfully decoded across both induction modalities using five different linear multivariate regression models. Although significant, decoding from scenarios was less successful than from movies, likely due to their more imaginative nature. In particular, decoding arousal from scenarios only showed low predictive utility. Representations of arousal and valence were widespread throughout the brain, and we reveal cerebellar and brainstem contributions that have largely been absent in past fMRI decoding studies. These findings clarify the distributed neural basis of arousal and valence and provide a foundation for future clinical research on the role of these constructs in affective dysregulation.
While the influence of state-dependent factors on appetitive processing has received considerable attention, the role of stable personality traits remains comparatively unexplored. Extraversion, characterized by heightened positive emotionality, represents a compelling candidate in this regard, as it may shape individual differences in Positive Valence System (PVS) functioning. The present study examined how extraversion modulates neural and subjective responses to pleasant stimuli; the role of neuroticism was additionally explored, given its established association with affective reactivity. Sixty-eight Italian university students (40 females) completed an online version of the Big Five Inventory (BFI-44) before the laboratory session. Then, participants completed a passive viewing task of pleasant and neutral images while undergoing an electroencephalographic (EEG) recording. Appetitive stimulus processing was indexed by the peak amplitude of the P300-LPP complex and subjective SAM ratings. Results revealed that extraversion was positively associated with larger P300-LPP complex amplitudes to pleasant relative to neutral stimuli and with higher arousal ratings across both emotional categories. Additionally, neuroticism was associated with lower valence ratings regardless of stimulus category, with no significant effect on neural responses to emotional stimuli. These findings highlight extraversion as a stable personality trait shaping PVS functioning. Specifically, low extraversion was associated with reduced P300–LPP amplitudes and lower arousal ratings to pleasant stimuli, paralleling neural patterns documented in psychopathological conditions involving blunted PVS activation. These results underscore the utility of ERP-based measures in capturing personality-related differences in appetitive processing relevant to psychopathology risk.
This dataset contains imageability and familiarity ratings for Ukrainian and English work-related proverbs collected from Ukrainian university students. The data were gathered as part of a cross-linguistic study examining how bodily grounding influences the mental imagery associated with proverbial expressions in a first language (L1) and a second language (L2). The participants (N = 49) were students at Vasyl’ Stus Donetsk National University. Ukrainian was their first language (L1), and English was their second language (L2). Participants evaluated Ukrainian and English work-related proverbs using 7-point Likert scales measuring imageability and familiarity. The stimulus set consisted of two proverb categories: body-based (BOD) proverbs containing explicit references to bodily actions, body parts, or sensorimotor experiences, and abstract (ABS) proverbs expressing work-related meanings without direct bodily imagery. Ratings were collected separately for Ukrainian and English proverb sets. The dataset includes raw participant responses, worksheet-level calculations, category means, language-specific means, and derived variables used for hypothesis testing. Statistical calculations included comparisons between BOD and ABS proverb categories as well as between L1 and L2 proverb processing. All participant data are fully anonymized. No personally identifiable information is included. The dataset may be useful for research on embodied cognition, conceptual metaphor theory, psycholinguistics, figurative language processing, proverb comprehension, imageability, familiarity, and cross-linguistic studies of language representation. File contents • Raw imageability ratings for Ukrainian proverbs • Raw imageability ratings for English proverbs • Raw familiarity ratings for Ukrainian proverbs • Raw familiarity ratings for English proverbs • Calculated category means (BOD and ABS) • Derived variables for hypothesis testing (H1–H3) • Statistical summary tables Variables Participant_ID – anonymous participant identifier Proverb_Rating – participant rating assigned to a proverb Imageability – perceived ease of forming a mental image (1–7) Familiarity – perceived familiarity with the proverb (1–7) Language – Ukrainian (L1) or English (L2) Category – Body-Based (BOD) or Abstract (ABS) Mean_Score – average score calculated for a participant, proverb category, or language condition License CC BY 4.0
By studying how individuals in an "at-risk" state of psychosis learn about threat and safety cues - specifically, how they develop and unlearn fear responses to neutral cues - we might better understand the mechanisms leading to heightened arousal and fear that are characteristic of acute psychotic episodes. At-risk individuals (N = 88; of which 28 fulfilled ultra-high-risk criteria on the Comprehensive Assessment of At-Risk Mental States interview and 60 scored above a predefined threshold on the Community Assessment of Psychic Experiences) and healthy controls (N = 44) underwent a standardized and validated differential fear conditioning paradigm including an acquisition, generalization, and extinction phase. The main outcomes of interest were the late positive potential, fear-potentiated startle, and self-reported ratings of valence, arousal, fear, and expectancy elicited by the conditioned stimuli (CS). The at-risk group exhibited diminished fear learning, evident in significantly reduced differentiation between the CS+ vs. CS- in the valence ratings compared to controls. Additionally, they demonstrated impaired fear extinction, evident in valence and arousal ratings, in which their CS differentiation showed a slower reduction than the controls. There were no group differences in late positive potential responses. At risk mental states appear to be associated with problems in distinguishing dangerous from safe stimuli and a diminished ability to adjust affective responses to conditioned stimuli based on new information, while the late-positive potential and fear-potentiated startle are unaltered. Early interventions could focus on recalibrating subjective emotional evaluations of fear-associated events.
This study investigates the influence of three biophilic interior design variables: natural light, interior vegetation (vertical green wall), and biomorphic form (biomorphic wall panel) on affective and physiological responses in a design studio interior utilizing immersive virtual reality (IVR) and wearable biofeedback technology. This study was a within-participant 23 factorial design that included one baseline and eight IVR studio conditions. Participants experienced all conditions while reporting affects using the Self-Assessment Manikin (SAM) valence and arousal scales, electrodermal activity (EDA), and skin temperature (ST). Cybersickness was measured with the Simulator Sickness Questionnaire (SSQ) and presence was assessed using the Igroup Presence Questionnaire and Slater-Usoh-Steed presence measures (IPQ, SUS), while baseline anxiety (STAI) was controlled. The results demonstrated a significant primary influence of natural light on SAM valence ratings: conditions with natural light were evaluated as more pleasant than the non-variable and baseline condition, whereas interior vegetation and biomorphic form had smaller, context-dependent effects that were most evident when layered with natural light. Differences in SAM arousal ratings were modest and non-systematic. EDA did not differentiate, and ST showed only small shifts, indicating that during calm exploratory monitoring, subjective affect was more responsive. The circumplex findings guided to an activity-specific zoned interior rather than a single uniform design studio.
This page contains behavioral data of an encoding and a temporal memory task in two experiments. Experiment 2 also includes an emotional valence rating that was conducted at the end of the experiment. For information about the study, please see the published manuscript in Psychological Research.
<p>For Arabic-English bilingual students, writing is a particularly challenging task, as it requires learning how to produce meaning through written scripts, distinctively different from those of the mother tongue. In this study, subjective familiarity ratings and vocabulary knowledge scores of the printed words of the Peabody Picture Vocabulary Test (PPVT) were collected from native Arabic speakers whose English proficiency was at least at the competent-user level (as per International English Language Testing System [IELTS] criteria). This level of competency is generally the precondition for admission of second-language learners to English-medium universities. The aim of the study was two-fold: (a) to determine the information upon which participants’ vocabulary knowledge relies through an examination of the extent to which such knowledge is predicted by key subjective and objective word properties; and (b) to assess the degree to which participants’ vocabulary knowledge, estimated from printed word comprehension (WC), is related to second-language students’ writing performance, as well as writing anxiety. In this study, objective word properties (e.g., frequency counts and the number of semantic neighbors), as well as subjective familiarity ratings of printed words, notably contributed to vocabulary knowledge (as indexed by WC scores). Furthermore, participants’ vocabulary knowledge was related to writing performance, as well as writing anxiety. Thus, the printed words of the PPVT could be used to predict not only the vocabulary knowledge of Arabic-English speakers admitted to university-level courses but also writing difficulties, thereby informing selective preemptive interventions.</p>
We describe THIVLVC, a two-stage system for the EvaLatin 2026 Dependency Parsing task.Given a Latin sentence, we retrieve structurally similar entries from the CIRCSE treebank using sentence length and POS n-gram similarity, then prompt a large language model to refine the baseline parse from UDPipe using the retrieved examples and UD annotation guidelines.We submit two configurations: one without retrieval and one with retrieval (RAG).On poetry (Seneca), THIVLVC improves CLAS by +17 points over the UDPipe baseline; on prose (Thomas Aquinas), the gain is +1.5 CLAS.A double-blind error analysis of 300 divergences between our system and the gold standard reveals that, among unanimous annotator decisions, 53.3% favour THIVLVC, showing annotation inconsistencies both within and across treebanks.
As large language models (LLMs) are increasingly integrated into daily life, in roles ranging from high-stakes decision support to companionship, understanding their behavioral dispositions becomes critical. A growing literature uses psychometric inventories and cognitive paradigms to profile LLM dispositions. However, these approaches cannot determine whether behavioral differences reflect stable, stimulus-specific individuality or global response biases and stochastic noise. Here, we apply crossed random-effects models -- widely used in psychometrics to separate systematic effects -- to 74.9 million ratings provided by 10 open-weight LLMs for over 100,000 words across 14 psycholinguistic norms. On average, 16.9% of variance is attributable to stimulus-specific individuality, robustly exceeding a statistical null model. Cross-norm prediction analyses reveal this individuality as a coherent fingerprint, unique to each model. These results identify individual differences among LLMs that cannot be attributed to response biases or stochastic noise. We term these differences machine individuality.
The majority of secondary school pupils in Tanzania are multilingual, speaking at least three languages which include: ethnic community language (there are currently more than 120 of them), (Ki)swahili, the national and first official language and, at varying levels of competency, English which is accorded the status of second official language. A very small number of pupils have access to French, since the language is taught only in a few schools as an optional subject. In public primary schools, pupils are generally bilingual, speaking their ethnic community language and (Ki) swahili. Due to their bilingual/multilingual knowledge, they are expected to activate each of the languages in their repertoire according to the situation of communication and to its level of formality as well as to the purpose of communication, the participants and their various characteristics, identity factors, etc. However, in certain institutional settings, the activation of the language repertoire is determined by the norms established by the schools. This paper is intended to: firstly, describe the formation of the bi/multilingual repertoire of Tanzanian primary and secondary school pupils and the nature of their language practices outside of school settings; secondly, indicate how the language practices are modified by the school and, thirdly, explain the ideological and/or pedagogical origins of the linguistic norms set by schools. The conclusion will attempt to explain the impact of the linguistic norms on the perception that the pupils have about the different languages in contact.
The study explores the reflection of politeness strategies in the translation process, focusing on English source texts and on their Uzbek translations. Using Brown and Levinson`s (1987) framework of positive and negative politeness, the research examines how translators preserve, adapt or omit these strategies in several contexts. The findings indicate that positive politeness strategies are more frequently maintained, whereas negative politeness often undergoes modification to suit Uzbek cultural and linguistic norms. The study highlights the importance of cultural and pragmatic sensitivity in translation.
Textbooks are fundamental educational tools that not only deliver curricular content but also convey societal and linguistic values. In the context of minority language education, textbooks have particular significance, as students’ language attitudes, identity, and self-perception are closely linked to the status and presentation of their native language. Language ideologies—often implicit beliefs about language and its use—shape how communities perceive linguistic norms, varieties, and speakers.
This article examines the protection of the Azerbaijani language in the context of globalization and digitalization as a priority area of public policy from a scientific and analytical perspective. The study analyzes the interaction of languages in the modern information environment, the impact of social media and digital technologies on national languages, and the opportunities and risks posed to the Azerbaijani language. The role of language in protecting national identity, statehood, and national-spiritual values through state programs, decrees, and orders, as well as legal and institutional mechanisms, is substantiated. The article highlights measures taken to strengthen the position of the Azerbaijani language in the digital environment, improve the terminology system, protect linguistic norms in the media and educational environment, and address existing risks. The study demonstrates that protecting the Azerbaijani language is not only a cultural issue but also has strategic significance in terms of national security, national identity, and statehood.
Language-model representations provide structured, high-dimensional annotations of naturalistic language stimuli and can serve as informative neural predictors during comprehension. We analyzed locked derived data from Brain Treebank, MEG-MASC, and Podcast ECoG with eight frozen language models, blocked encoding models, and matched temporal, nuisance, and representation-capacity controls. Positive held-out prediction and gains over low-level baselines were widespread in source-level summaries. Across Brain Treebank and Podcast ECoG, 67 of 432 evaluable rows met a controlled predictive-only criterion, and model-side feature ablations changed prediction scores in most evaluable source rows. Brain-derived, timing-linked, acoustic, and implanted-signal controls confirmed component-level sensitivity of the analysis pipeline. These findings show that language-model-derived quantities can annotate neural activity during natural speech and text comprehension. Participant-level matched-control advantages were localized rather than uniform, response-profile and feature-specificity contrasts bounded representational or computational interpretations, and complete co-indexed integrated interpretation will require future jointly indexed coverage. Together, the analyses identify language-model features as useful neural predictors and separate predictive usefulness from claims about shared neural organization or language-processing computations.
ABSTRACT The widespread use of TikTok among elementary school students has brought noticeable changes to the way children communicate in their daily lives. The platform is no longer used merely as a source of digital entertainment, but has also begun to shape students’ word choices, speaking styles, and language habits. This condition can be observed among students at MIS Al-Khairaat Pombewe, who have become increasingly familiar with viral expressions, popular abbreviations, slang, and the mixing of Indonesian with foreign languages in everyday conversations. Such circumstances have raised concerns regarding the declining use of proper and standard Indonesian within the school environment. This study employed a descriptive qualitative approach involving the principal, teachers, and students selected purposively as research informants. Data were collected through observations, interviews, and documentation, then analyzed through the stages of data reduction, data presentation, and conclusion drawing. The findings reveal that TikTok exerts a dual influence on children’s language development. On the one hand, the platform contributes to vocabulary expansion, enhances students’ creativity in language use, and broadens their digital knowledge. On the other hand, the intensity of TikTok usage encourages the frequent use of informal language in formal situations, leading to a gradual decline in the use of proper Indonesian according to linguistic norms. Therefore, the involvement of teachers and parents is necessary to guide children toward wiser social media use without neglecting the development of their language abilities. ABSTRAK Fenomena penggunaan TikTok di lingkungan sekolah dasar memperlihatkan perubahan yang cukup nyata pada cara siswa berkomunikasi sehari-hari. Platform ini tidak lagi sekadar dimanfaatkan sebagai hiburan digital, tetapi turut membentuk pilihan kata, gaya berbicara, hingga kebiasaan berbahasa anak. Kondisi tersebut terlihat pada siswa MIS Al-Khairaat Pombewe yang semakin akrab dengan istilah viral, singkatan populer, bahasa gaul, serta pencampuran bahasa Indonesia dengan bahasa asing dalam percakapan mereka. Situasi ini memunculkan perhatian terhadap menurunnya penggunaan bahasa Indonesia yang baik dan benar di lingkungan sekolah. Kajian ini memanfaatkan pendekatan deskriptif kualitatif dengan melibatkan kepala sekolah, guru, dan siswa sebagai informan yang dipilih secara purposive. Informasi penelitian diperoleh melalui observasi, wawancara, dan dokumentasi, kemudian dipahami melalui tahapan reduksi data, penyajian data, dan penarikan kesimpulan. Temuan penelitian memperlihatkan bahwa TikTok memberi pengaruh ganda terhadap perkembangan bahasa anak. Di satu sisi, media sosial tersebut membantu siswa memperluas kosakata, meningkatkan kreativitas dalam berbahasa, dan memperkaya wawasan digital mereka. Di sisi lain, intensitas penggunaan TikTok ikut mendorong penggunaan bahasa informal dalam situasi formal sehingga kebiasaan menggunakan bahasa Indonesia sesuai kaidah menjadi semakin berkurang. Karena itu, keterlibatan guru dan orang tua dibutuhkan agar penggunaan media sosial dapat diarahkan secara lebih bijak tanpa mengabaikan perkembangan kemampuan berbahasa siswa.
The authors see the purpose of the study as a comparative analysis of political discourse on the example of D. Trump’s speeches during his election campaigns in 2016 and 2024. The scientific novelty lies in the confirmation of the concept of using language as a weapon, which acts in Trump’s speeches as a tool to manipulate and control people through different discursive means and in different periods of time. Comparing the changes that discourse has undergone over time allowed the authors to analyse the priorities that reflect the general political tendency for positive emotional encouragement rather than threats and aggression. The relevance of this article is determined by the shift that has occurred in political discourse, which requires a rethinking of how the political actors select linguistic norms and how this selection will affect the formation of modern political language.
Cet article présente la dernière version du treebank Rhapsodie, un corpus de français parlé multi-genres annoté en syntaxe et prosodie. Les deux principales innovations sont une annotation morphosyntaxique réellement basée sur la version orale du corpus (ce qui est prononcé) et non sur sa transcription orthographique et une intégration de l’ensemble des niveaux d’annotations, syntaxe, prosodie et métadonnées, dans une même structure, permettant ainsi des requêtes croisées.
The study explores the attitudes and opinions of Pakistani English teachers on Standard British English (SBE) and Standard American English (SAE). Although most studies have been done on learner attitudes, this paper refracts the same to the teacher, whose role is very important in influencing linguistic norms in EFL. A survey involving 60 English teachers in the government and privately owned institutions in Pakistan was conducted using a mixed-method approach, whereby a questionnaire, which included closed-ended and open-ended questions, was used to gather the data. The results indicate that there is an acute effect of academic preparation of teachers, exposure to media, and the practices of the institution on the preference of variety among the teachers. The paper also examines the relationships between the linguistic backgrounds and pedagogical decision-making amongst teachers. The findings can be added to the current discussion of World Englishes and can be applied to the teaching training and language policy in Pakistan.
This study investigates whether the relationship between word-level stress detection and musical aptitude differs across first-language (L1) backgrounds.While prior work has shown that musical aptitude predicts prosodic sensitivity, it remains unclear whether this relationship is modulated by linguistic experience.Sixty intermediate-to-advanced learners of Spanish (20 German, 20 French, 20 Korean) completed an odd-one-out stress discrimination task and the Mini-PROMS musical aptitude test assessing Melody, Accent, Tempo, and Tuning.Spanish word-familiarity ratings served as a proficiency control.Results showed that German learners outperformed Korean and French participants, consistent with cross-linguistic differences in the use of lexical stress.Among the musical subtests, only Melody significantly related to stress discrimination across all L1s, suggesting a shared sensitivity to pitch variation.The Accent score interacted with L1, showing a positive trend for German and French learners but not for Korean participants.No effects emerged for Tuning or Tempo.These findings indicate that pitch-related perceptual skills, rather than rhythmic or timbral ones, relate to stress sensitivity in L2 Spanish, highlighting the role of specific musical dimensions in prosodic learning.
This chapter explores how artificial intelligence (AI) tools mediate the identity development, emotional labor, and academic adaptation of international students in U.S. higher education. Framed through the lenses of intersectionality, resilience, and self-authorship, the chapter draws on duoethnography to examine how AI is used not merely as a technical aid but as a scaffold for rewriting the self in unfamiliar academic terrain. While AI offers immediate access to academic conventions, its reliance on dominant linguistic norms often flattens cultural expression and obscures opportunities for deeper growth. Through personal narrative, peer reflection, and theoretical analysis, this chapter interrogates what is gained and what is lost when AI supplements or replaces human-centered support systems. It argues that international student engagement with AI reveals a broader story about survival, belonging, and identity negotiation in an increasingly technologized and globalized university landscape.
Natural animal sounds can be perceived as "harsh" or "buzzy"-sound descriptions known as auditory roughness. In this study, the association between the human emotional appraisal of animal vocalizations and the perceived roughness was examined across three sound categories-mammals, birds, and insects. Ninety 1-s vocalizations (30 per category) were rated online by two independent groups: one judged perceived roughness, the other judged valence and arousal. Perceived roughness showed a strong negative correlation with valence (rougher sounds were judged more negatively). No clear link between roughness and arousal emerged (no correlation for birds and mammals, and a small one for insects) probably because of the homogeneity of the arousal ratings. Acoustic analyses showed that a variability measure derived from the modulation power spectrum tracked perceived roughness and, inversely, valence within and across categories. Together, these results indicate that humans systematically interpret rough sounds, irrespective of their source species, as cues of negative valence. We propose that roughness is an ecologically meaningful auditory code that drives emotional responses to animal sounds in humans.
Abstract Research on how non-natives process and learn binomials ( black and white ) is limited. The present study addresses this gap using online (eye-tracking) and offline (familiarity rating) tasks. Sixty non-native speakers of English (L1 = Arabic) read six stories seeded with 21 novel binomials in three conditions: one exposure, six exposures, and no exposure (i.e., only in post-test) in a counter-balanced design. Each item was also presented in the reversed order ( white and black ). The non-natives read the stories as their eye movements were monitored and answered comprehension questions. In addition to the novel binomials, 12 existing binomials (congruent with Arabic) were included in the passages as a baseline for comparison. After completing the reading task, the participants completed an offline rating task as a measure of declarative knowledge of the binomial configuration (i.e., word order). All items were rated twice, once in the forward direction and once in the reversed direction. Online results showed that non-natives were not sensitive to the configuration of existing binomials, and there was limited evidence of any sensitivity to novel binomials. Offline, non-natives showed sensitivity to the configuration restrictions of existing binomials but not novel ones.
The article explores the dynamics of the Russian orthographic system within the framework of the permanent opposition between historical traditions and modern cognitive- communicative realities. The author subjects to critical analysis the key stages in the evolution of Russian spelling, the mechanisms of academic codification of the linguistic norm, and the determining impact of global digitalization on the 21st-century written culture. The paper theoretically substantiates the inevitability of adapting orthographic rules to the requirements of expressiveness, compression, and polycodality in network discourse. Based on diachronic analysis and empirical research of electronic texts, the author's classification of modern orthographic deviations is proposed, and prognostic models for the development of Russian graphics are developed. The scientific and practical value of the work lies in the substantiation of an adaptive approach to codification, which helps maintain a balance between the systemic stability of the language and its functional flexibility. Keywords: Russian spelling, orthographic norm, linguistic evolution, internet linguistics, codification, academic rules, linguistic tradition, digital communication, translingual practices.
Abstract: The integration of artificial intelligence (AI) into English as a Foreign Language (EFL) education has brought about transformative changes in how learners develop intercultural communicative competence (ICC). This systematic literature review examines how AI-mediated language production and adaptive feedback mechanisms reshape ICC among EFL learners. Following PRISMA guidelines, this study analysed 35 peer-reviewed articles published between 2020 and 2025. The review focuses on ELT-relevant dimensions, including automated writing evaluation, generative AI in language learning, and AI-mediated cross-cultural exchange. Findings indicate that AI facilitates ICC by providing real-time adaptive feedback that helps learners negotiate cultural nuances and linguistic norms. The study concludes that AI serves as a "cultural mediator," offering a triadic interaction model that enhances learners' knowledge, skills, and attitudes in intercultural settings.
Multilingualism is defined as a mode of communication in contemporary world. The multilingualism teaches us the important values to understand the context. This study analyzes dual point of view about the multilingualism: the foreign languages that appear in it, i.e. explicit multilingualism and the universal aspect or hidden languages that are indirectly described, i.e. implicit multilingualism. Thismay comprise linguistic norms, reader and text interaction, among others. The aim of this study is to highlight the impacts of elements of multilingualism used in Amélie Nothomb’s novels. It focuses essentially on the works of the contemporary Francophone writer, notably, Amélie Nothomb. She articulates the enriching elements of multilingualism in French and Japanese languages through herwritings. Her breakthrough works mainly articulate the diversity of multilingualism and also the essential meaning of understanding the different elements or expressions related to the French and Japanese language through the richness of culture from a geographical point of view and also the other elements. These elements are articulated about expressions which show the impact ofmultilingualism in her writings that refer either to French, Japanese, or other languages.
Child-directed fingerspelling is an approach used by Deaf parents for communication, language, and literacy development. This study reports on findings from a qualitative intrinsic case study aimed at understanding how Deaf parents use fingerspelling with their young children. The research questions were: (1) What are the cultural beliefs of Deaf parents regarding fingerspelling with young children? (2) What are their patterns of use of child-directed fingerspelling in natural settings? Twenty-one Deaf families with 27 deaf children ages 5 years and under were interviewed via recorded Zoom meetings conducted in American Sign Language. Data were analyzed using grounded theory to develop a new theoretical contribution with the core category: Deaf families socialize their children into Deaf visual-linguistic norms through fingerspelling. This new theoretical insight aligns with Holcomb's Deaf epistemological framework (2010) and Ochs and Schieffelin's (2008, 2011) language socialization theory. Limitations and recommendations for future research are also included.
This paper examines how artificial intelligence (AI), machine learning algorithms, and automated digital systems shape linguistic practices, reinforce or challenge linguistic hierarchies, and influence communication in contemporary society. As digital platforms increasingly mediate human interaction, algorithms determine what content becomes visible, which linguistic varieties are privileged, and how users adapt their language to gain visibility and engagement. The study explores algorithmic bias in search engines, social media feeds, voice assistants, and automated moderation systems, highlighting how these technologies reproduce existing social inequalities related to class, caste, gender, and ethnicity. Drawing on sociolinguistic theories of language ideology, linguistic capital, and digital discourse, the paper argues that AI-driven communication environments are not neutral but deeply ideological. They shape linguistic norms, influence identity performance, and regulate public discourse. The findings underscore the need for critical sociolinguistic engagement with AI systems to ensure equitable, inclusive, and culturally sensitive digital communication.
This study explores Australian language teachers’ familiarity with and attitudes towards gender-inclusive language (GIL) in the classroom. Through a mixed-methods approach combining survey data from 51 teachers and interviews with 6 participants, the research examines teachers’ understanding of GIL, their views on its implementation and perceived challenges. Findings reveal that while most teachers are familiar with GIL, this knowledge often comes from informal sources rather than teacher education. Most teachers express positive attitudes towards incorporating GIL, viewing it as important for student inclusivity and identity affirmation. However, a spectrum of perspectives emerges, ranging from enthusiastic adoption to resistance based on ideological and/or pedagogical concerns. Key challenges identified include a lack of standardisation, limited resources and training and tensions between inclusive practices and assessment requirements. The study highlights the complex interplay between teachers’ personal beliefs, pedagogical challenges and evolving linguistic norms in shaping GIL implementation, emphasising the need for targeted professional development, clearer curriculum guidance and ongoing dialogue to support teachers in navigating gender-expansive practices.
SRC, an acronym for Stimulus-response correlation, refers to determining the relationship between stimulus and corresponding brain responses. The neural aesthetic resonance hypothesis proposes that the level of enjoyment or familiarity can be distinguishable based on the relationship between stimulus and brain responses. To test this hypothesis, we use EEG data of 20 participants listening to 12 songs with their enjoyment and familiarity ratings. We aim to classify the low and high ratings of familiarity and enjoyment based on SRC. Eighteen musical features are extracted and transformed into the first principal component (PC1). In addition, root mean square (RMS) and spectral flux are used for analysis. Canonical Correlation Analysis (CCA), an unsupervised AI optimization method, is employed to compute the SRC between musical features and ten regions of brain responses, followed by considering four principal CCA features for classification using the Random Forest classifier with cross-subject evaluation. Our results demonstrate that the right frontal and right parietal regions provide significant predictive ability. Our empirical finding suggests that RMS features preserve the predictive ability for familiarity, whereas PC1 is for enjoyment prediction. Maximum familiarity and enjoyment accuracy reach nearly 76% and 73% accuracy. This work leverages AI techniques to decode sensor-derived neural signals, advancing real-time applications in affective computing and wearable EEG devices.
This study investigates the linguistic and communicative functions of abbreviations in English and Karakalpak advertising discourse, focusing on how these compressed forms contribute to message efficiency, stylistic expression, and cultural positioning. Although abbreviations are widely used across global advertising, their structural patterns and pragmatic roles vary according to linguistic norms and audience expectations. Therefore, the research employs a mixed qualitative methodology integrating structural analysis, discourse interpretation, and comparative linguistics. The results demonstrate that English advertising makes extensive and creative use of acronyms, initialisms, blends, and hybrid forms to construct modern, technologically oriented, and globally recognizable brand identities. In contrast, Karakalpak advertising relies more on functional initialisms and borrowed English abbreviations, reflecting both local communicative preferences and growing global influence. The discussion interprets these findings within broader socio-cultural and economic contexts, revealing that abbreviation usage serves as a marker of globalization, cultural continuity, and linguistic innovation. Ultimately, the study contributes to a deeper understanding of how abbreviated forms shape contemporary advertising communication in multilingual environments.
Pre-trained language models (PLMs) achieve high accuracy on standard benchmarks for sentiment analysis. However, this performance can hide systematic weaknesses in determining the sentiment of negated sentences, for example when the phrase “not good” is still classified as positive. In this study, we use sentiment classification of English movie reviews in the Stanford Sentiment Treebank 2 (SST-2) as a case study to specifically examine and improve how BERT handles negated sentences. We perform a brief additional fine-tuning of the existing BERT model on a small, automatically constructed set of lexicon-based counterfactual examples that target simple lexical negation. Experimental results on carefully paired original-negated sentences show that this procedure substantially reduces prediction errors on negated inputs while leaving overall performance on SST-2 almost unchanged.
<p>The purpose of this study is to identify the specific features of applying folk pedagogy in developing communicative competence among students of nonlinguistic specializations and to assess its effectiveness in foreign language teaching. The methodology involves student surveys, educator questionnaires and interviews, a pedagogical experiment within educational institutions, and a Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis of the data obtained. Both quantitative and qualitative data collection methods are employed, enabling a comprehensive evaluation of the proposed approach. The main findings demonstrate a positive impact of folk pedagogy on the acquisition of linguistic norms, increased student motivation, and the development of communicative skills. The proposed approaches may contribute to improving the quality of language training and expanding the range of methodological tools available in foreign language education. The practical value of the study lies in the potential to integrate folk pedagogy into the foreign language learning process, which may enhance material acquisition and promote deeper cultural understanding. The recommendations offered could be used to improve higher education curricula. The application of folk pedagogy supports a more engaging, interactive, and natural learning experience, aligning with current educational trends.</p>
This research explores the historical emergence of linguistic terminology in three languages—English, Uzbek, and Karakalpak—with special attention to the role of Latin, Greek, and Arabic heritage. It traces how borrowed concepts were nativized and localized in each linguistic setting. By juxtaposing five evolutionary stages in English with analogous processes in Uzbek and Karakalpak, the paper illustrates the interplay between international scholarly traditions and indigenous linguistic norms. The conclusions highlight both universal tendencies and language-specific particularities in the growth of terminological systems.