Papers reviewed and determined not to be word norm studies. Use the flag icon to report errors or suggest re-inclusion.
18265 papers
The study primarily focuses on identifying the limitations and inadequacies of media linguistics and internet linguistics, which can no longer comprehensively address the specifics of the modern informational landscape due to outdated scientific and theoretical frameworks. There arises a need for clear delineation of the conceptual boundaries of the aforementioned disciplines to prevent methodological ambivalence. Additionally, in response to these challenges, the development of a distinct discipline – newslinguistics, exclusively dedicated to the study of the news landscape – is proposed. Within this framework, its specialised subdiscipline, newsdiscourseology, is introduced to encompass the exploration of all aspects of digital news discourse. A central construct of this subdiscipline is the concept of the hypernews – a type of inclusive text characteristic exclusively of next-generation news platforms. Consequently, the establishment of newsdiscourseology is regarded as a critical response to the demands of the contemporary informational paradigm, characterised by hypertextual, interactive, polycoded, and multimodal structures. Further investigation of this issue entails the creation of a new scientific and practical foundation, including the identification and structured representation of implicit linguistic patterns embedded within contemporary digital news platforms. Assigning these patterns explicitness and specificity will contribute to enhancing users’ cultural and intellectual levels, fostering their critical thinking, and advancing related scientific practices. These developments will also enable the creation of sophisticated software utilities, integrated into browser-based linguistic applications and automated analytical-statistical linguistic databases. These innovations will furnish the foundation for the synchronous and automated analysis of hypernews, the formulation of strategies for optimising news content consumption, and ensure accessibility for a broad spectrum of users, ranging from system administrators to the general public. Pursuant to the proposed paradigm shift, continued exploration within the domain of digital informational communications offers significant transformative potential for addressing the complex challenges of the information age.
This study investigated the neurophysiological and affective responses elicited by nature-inspired indoor design elements, including curvilinear forms (CL), nature views (N), and wooden interiors (W), in a virtual environment, and their effects on cognitive performance. Thirty-six participants experienced one control and three experimental conditions in a within-subject design. Electroencephalography (EEG) was used to record neural activity, relaxation and valence ratings assessed affective states, and standardized tasks measured cognitive performance. The W condition elicited EEG patterns indicative of relaxed attentional engagement, including increased alpha-to-theta (ATR) and alpha-to-beta (ABR) ratios, and a decreased theta-to-beta (TBR) ratio. These neural patterns were associated with higher self-reported relaxation and positive affect, and with enhanced cognitive performance relative to the control condition. In contrast, the CL and N conditions did not improve cognitive performance, and the N condition showed elevated physiological arousal, likely due to heightened visual stimulation. Regression analysis identified ATR and relaxation as significant predictors of cognitive performance, emphasizing the role of emotional stability and neural balance in supporting task engagement. Overall, the findings highlight the potential of nature-inspired design to foster a synergy between psychological relaxation and cognitive attention, though further research is needed across diverse spatial typologies to isolate specific design parameters.
This article discusses the methods of morphological, syntactic, and semantic analysis used in natural language processing for the Uzbek language. The linguistic features of Uzbek – complex agglutinative morphology, free word order, and limited resources – necessitate a specialized approach and research in applying these methods [Senuma, Aizawa 2017, 100-109]. Within the framework of this study, morphological analysis methods, followed by syntactic and semantic analysis methods, were examined based on scientific sources. Each section presents the existing advantages and disadvantages, experiences in applying these methods to the Uzbek language, as well as comparative analyses with foreign languages. For morphological analysis in Uzbek, rule-based methods, statistical models (HMM, CRF, etc.), and neural network-based approaches (BiLSTM-CRF, seq2seq) are discussed, with results provided in examples and percentages. It is demonstrated that syntactic parsing is carried out using dependency and constituency parsing methods. The issue of constructing a UD treebank for the Uzbek language, which follows the SOV word order, has been examined. The impact of complex morphological structure and free word order in sentences on parser construction is highlighted. As a result of the studied approaches, the issue of building hybrid parsers, integrating them with morphological analysis, and feeding grammatical categories of words into the parser has been raised. Additionally, the development of neural constituency parsers based on neural networks and the effectiveness of their results were analyzed. For the subsequent analysis stage related to NLP, particularly in semantic and sentiment analysis, models ranging from Word2Vec and FastText, which represent word meanings in vector form, to context-adapted transformer models such as BERT, mBERT, and UzBERT were also discussed. The text also considers issues of high-level semantic role labeling and the creation of semantic networks such as WordNet and FrameNet. In evaluating NLP approaches for the Uzbek language, Uzbek is compared with other languages: English, Turkish, and Russian. The application of rule-based, statistical, and neural methods in these languages is examined, and the results of the analysis are presented.
This article explores gender-based language variation in English and Romanian through an analysis of two plays: Death of a Salesman by Arthur Miller and Frumoasa călătorie a urșilor panda povestită de un saxofonist care avea o iubită la Frankfurt by Matei Vișniec. The study investigates linguistic differences between men’s and women’s speech at the phonological, lexical, and grammatical levels while addressing broader sociolinguistic theories on gendered communication. The study concludes that women’s speech tends to be cooperative, marked by empathy and support, whereas men’s speech is often competitive, aiming to dominate conversations. Men’s interruptions and delayed minimal responses are used to control conversational topics, often leaving women silent. Notably, men’s use of repetitions reflects assertiveness in English but uncertainty in Romanian. This investigation highlights how gender-based language variation is influenced by social norms, cultural expectations, and contextual factors. By examining these distinctions, the study contributes to ongoing research in sociolinguistics, shedding light on how gender interacts with linguistic behavior across different languages and cultural contexts.
Background/Objectives: Obesity and insulin resistance (IR) increase the risk for mood disorders and may impair emotional experiences. This study investigated whether obesity and/or IR moderated the links between brain potentials and affective processing during young adulthood. Methods: Thirty young adults completed a passive picture-viewing task utilizing the International Affective Picture System while real-time electroencephalography was simultaneously recorded. Two event-related potential components—early posterior negativity (EPN) and late positive potential (LPP)—were quantified. Affective processing parameters included the mean valence ratings and stimulus-to-response-onset reaction times in response to unpleasant, pleasant, and neutral images. Body fat percentage and Homeostatic Model Assessment for Insulin Resistance values were measured. Hierarchical moderated regression analysis was utilized to test the interrelationships between brain potentials, adiposity, IR, and affective processing parameters. Results: In the Negative–Neutral valence condition, lean and insulin-sensitive participants gave less negative valence ratings to unpleasant versus neutral images when late-window LPP amplitudes were larger, whereas respective counterparts showed no such relationship. Contrariwise, obesity and IR did not moderate the links between LPP amplitudes and affective processing parameters in the Positive–Neutral or Negative–Positive conditions. Additionally, EPN amplitudes and affective processing scores were not moderated by obesity or IR across any of the valence conditions. Conclusions: Lean and insulin-sensitive young adults showed attenuated negative affective processing of unpleasant versus neutral stimuli through increased brain activity, whereas obese and insulin-resistant young adults did not. In contrast, obesity and IR did not modify the relationship between neural activity and positive affective processing in young adults.
Artificial intelligence (AI) models can sense subjective affective states from facial images. Although recent psychological studies have indicated that dimensional affective states of valence and arousal are systematically associated with facial expressions, no AI models have been developed to estimate these affective states from facial images based on empirical data. We developed a recurrent neural network-based AI model to estimate subjective valence and arousal states from facial images. We trained our model using a database containing participant valence/arousal states and facial images. Leave-one-out cross-validation supported the validity of the model for predicting subjective valence and arousal states. We further validated the effectiveness of the model by analyzing a dataset containing participant valence/arousal ratings and facial videos. The model predicted second-by-second valence and arousal states, with prediction performance comparable to that of FaceReader, a commercial AI model that estimates dimensional affective states based on a different approach. We constructed a graphical user interface to show real-time affective valence and arousal states by analyzing facial video data. Our model is the first distributable AI model for sensing affective valence and arousal from facial images/videos to be developed based on an empirical database; we anticipate that it will have many practical uses, such as in mental health monitoring and marketing research.
This preregistration describes a within-subjects experiment investigating whether and how cultural priming would influence emotional valence ratings among unbalanced Mandarin–English bilinguals immersed in an L2 environment. Participants rate positive, negative, and neutral words in three cultural contexts (no context, native culture, second culture). We hypothesise that activating either native or second culture will enhance the extremity of valence ratings, compared to the no context baseline, with stronger effects when the native (Chinese) culture is primed. Trial-level valence ratings will be analysed using a linear mixed-effects model with fixed effects of Culture, Valence, and their interaction.
Alexithymia is a multi-faceted personality trait associated with particularities in emotion processing and regulation. While alexithymia total scores have frequently been used to explain these particularities, recent models suggest a differentiated role of specific alexithymia facets at specific emotion processing stages. In this study, we investigated whether alexithymia total scores and facets moderate the effect of emotional salience on valence ratings, arousal ratings and correct emotion recognition. Ninety-four non-clinical participants provided valence and arousal ratings as well as discrete emotion labels for 160 pictures of emotional facial expressions varying in morphing intensity (40%, 60%, 80% and 100% emotion intensity) and discrete emotion type (happy, angry, disgusted, sad, fearful). Alexithymia levels were measured with the Toronto Alexithymia Scale (TAS-20). Our results show that alexithymia total scores moderate arousal and emotion recognition at lower salience levels. Higher alexithymia total scores were associated with higher arousal ratings and higher emotion recognition probability, but only at 40% morphing intensity, which partially supports the over-responding model of alexithymia. In addition, we found contrasted effects of alexithymia facets. Taken together, these results highlight the importance of focusing on emotional salience perception in alexithymia.
This resource contains a cross-linguistic lexical database comprising more than 2.6 million entries from over 8,000 languages and dialects worldwide. The dataset is enriched with Glottolog classification data and additional genealogical metadata, enabling large-scale comparative and typological analyses. A subset of the vocabulary has been grouped into higher-level semantic categories to facilitate macro-typological and semantic investigations. The present public extract includes only those components suitable for open dissemination. Additional internal structural layers — most notably the phonological slot structures (K1/K2/K3) — were designed for custom Python programs and must be extracted or reconstructed separately depending on the research focus. This work operates at the intersection of: genealogical and historical-comparative linguistics, etymological research, sound symbolism and sound–meaning correspondences, philosophy of language and epistemology. Special attention is given to the relationship between linguistic development and the development of consciousness, and to the question of how extensive empirical data may contribute to an epistemic approach to these foundational issues. A comprehensive monograph as well as several research papers are currently in preparation and will be linked here once available.
This study characterize mood and emotional regulation in women with premenstrual syndrome (PMS) using near-infrared spectroscopy (NIRS) and mood assessments. Hemodynamic responses in the prefrontal cortex (PFC) were measured while participants viewed emotion-inducing images during both the follicular and luteal phases of the menstrual cycle. Emotional valence and arousal ratings for each image were obtained immediately after the task. In addition, mood states were evaluated prior to the task using the Profile of Mood States Second Edition (POMS2). Forty-six women completed the procedures across both menstrual cycle phases. After excluding five participants diagnosed with premenstrual dysphoric disorder (PMDD), data from 41 participants (non-PMS: n = 25, PMS: n = 16) were analyzed. During the follicular and luteal phases, the PMS group showed significantly lower integrated oxyhemoglobin (oxy-Hb) responses to positive emotional stimuli in the right prefrontal region compared to the non-PMS group (follicular phase: p =.03, r = 0.35; luteal phase: p <.001, r =.0.52). These r values represent effect sizes (rank-biserial correlations) corresponding to the Mann–Whitney U tests. No significant group differences were found in the left prefrontal region and response to negative stimuli. Based on POMS2 scores, the PMS group showed significantly higher scores on six negative mood scales and a lower score on one positive mood scale during the follicular phase. During the luteal phase, only one negative mood subscale score was significantly higher in the PMS group. Group differences in subjective emotional valence and arousal ratings were evident only during the follicular phase. These findings suggest that women with PMS exhibit attenuated neural responses to positive emotional stimuli and altered mood states even during the follicular phase when symptoms are often not consciously recognized. This may highlight the possibility that early-phase emotional dysregulation may precede overt symptom manifestation in PMS, providing insights into its temporal dynamics.
The concordance between subjective and facial hedonic responses while eating is informative, both practically and theoretically. Recent psychophysiological studies reported that hedonic ratings during the consumption of gel-type food were negatively associated with facial electromyography (EMG) signals recorded from the corrugator supercilii and positively associated with those from chewing-related muscles. However, the relationships were tested in a static manner, and the dynamic subjective–facial concordance remains untested. Therefore, we investigated this by assessing participants’ dynamic valence ratings and recording their facial EMG from the corrugator supercilii, zygomatic major, masseter, and suprahyoid muscles while they chewed and swallowed gel-type food stimuli of various flavors. Cross-correlations with dynamic valence ratings were negative for corrugator supercilii EMG signals and positive for zygomatic major, masseter, and suprahyoid EMG signals during both chewing and swallowing. These findings indicate that subjective hedonic experiences and facial EMG signals are dynamically coupled. • Participants chewed and swallowed gel-type food stimuli of various flavors. • We measured their dynamic valence ratings and facial EMG (e.g., the corrugator supercilii). • Cross-correlations between valence ratings and EMG signals were found while chewing. • Similar cross-correlations between valence ratings and EMG signals were found while swallowing.
This paper proposes the S M Nazmuz Sakib Event–Nesting Hypothesis for Bangladiscourse and introduces two quantitative notions: the Sakib Cohesion Constantand the Sakib Bangla Narrative Cohesion Index (S–BNCI). The hypothesis statesthat, in Bangla narrative and expository prose, there is a systematic local trade–off between (i) event chaining realised by serial and conjunctive–participle verbsequences and (ii) propositional nesting realised by finite complement clauses introduced by the complementizer je. Building on resources such as the Bangla RSTDiscourse Treebank [1, 2], DiMLex–Bangla [3] and Universal Dependencies treebanks for Bengali [5, 6, 7], the paper formulates S–BNCI as a windowed indexcombining densities of serial verbs, je–complements, discourse particles, discourseconnectives and zero subjects. The Sakib Cohesion Constant is defined as the negative slope parameter linking event–chain density to the probability of embedded complement clauses in a logistic regression model over local windows. Using corpusstatistics reported for Bangla RST–DT, DiMLex–Bangla and UD_Bengali–BRU,we present fifteen genuinely data–based illustrations that anchor the ranges of theproposed parameters and show how Bangla grammar distributes resources betweenevent chaining and embedding. The proposal is positioned as a falsifiable, computationally testable hypothesis and is, to the best of current bibliographic knowledge,not explicitly formulated in prior work on Bangla cohesion, serial verb constructionsor complementizer placement [8, 9, 10, 11, 4].
Abstract Cannabis imagery is proliferating online and can elicit affective responses related to use. Scalable tools are needed to evaluate how this proliferation could influence population health. This pilot study tested whether multimodal generative artificial intelligence (MGAI) can reproduce subjective human affect ratings of cannabis images. Four MGAI agents (model: gpt-4o-2024-11-20) were created to parallel the four human participant subgroups from Macatee et al. 2021, defined by primary method of cannabis administration (bong, bowl, joint/blunt, vaporizer). Using Macatee et al.’s participant instructions and standardized image set, each agent rated images of its primary method of administration on valence, arousal, and urge constructs. For each image-construct pair, n=100 ratings were generated in separate conversational threads using zero-shot prompting. Image-level MGAI mean ratings were compared with human mean ratings using Two One-Sided Tests of equivalence and Spearman correlations. Although formal statistical equivalence was rare (4% valence, 11% arousal, 3% urge), MGAI ratings approximated human ratings closely (Mean difference of mean ratings = – 0.31, SD = 1.23) and correlations between MGAI and human mean ratings were moderate to high: r s (valence) = 0.55, r s (arousal) = 0.34, r s (urge) = 0.56. MGAI also reproduced the parabolic relation between rating means and standard deviations observed in human data. These preliminary results indicate that MGAI can approximate human cannabis cue-reactivity patterns closely enough to justify continued refinement. MGAI could potentially be developed into a Cannabis Regulatory Science tool to aid regulatory oversight of online cannabis marketing.
The influence of lyrics on music aesthetics has long been a prominent research topic in the fields of aesthetics, musicology, and psychology.However, empirical studies have yielded inconsistent findings concerning the effects of lyrics.Accordingly, the present study examines the effect of lyrics on music aesthetics across historical periods.We selected representative popular music from the late 20th century, known as "era music", and representative popular music from the contemporary period, known as "modern music", both with and without lyrics, as materials.After listening to each music clip, participants sequentially completed aesthetic rating, preference rating, and familiarity rating tasks.We found that the aesthetic rating and its inter-subject correlation for era music with lyrics were significantly higher than those for the version without lyrics, while no significant difference was observed between the two versions of modern music.These results illustrate the era-dissociation effect of lyrics in music aesthetic ratings, suggesting the era-dissociation characteristics of lyrics and the difference in individual subjective aesthetic standards.
The aim of this study was to investigate the relationship between the categorical recognition of emotional facial expressions and two affective dimensions, arousal and valence, as well as other facial characteristics, such as gender and age. To achieve this goal, participants were asked to evaluate expressive faces from two databases (the Karolinska Directed Emotional Faces and FACES) along the dimensions of arousal and valence, in addition to completing an emotional categorization task. The results revealed variations in overall arousal and valence levels across different emotional categories. Most notably, they demonstrated that the three assessments were interdependent: the positive or negative valence of facial expressions was found to be a function of arousal level for all emotional category except surprise, whereas the accuracy of categorization into discrete categories was influenced by both arousal and valence level. Furthermore, the gender and age of the faces influenced evaluations across all three tasks - arousal ratings, valence ratings, and categorization. The implications of these findings for the study of facial emotion recognition mechanisms are discussed.
Interactive internet platforms allow speakers to comment on linguistic variation in utterances from around the world to which they are exposed. Digital platforms thus function not only as spaces for discussing linguistic usage but also as arenas for negotiating language norms. Participants in these discussions often adopt strongly asserted normative positions. In this context, a project developed at the University of Kiel is presented in the article. It aims to analyse such normative discourses from a comparative perspective, with the goal of highlighting the specificities of different linguistic cultures. The article draws attention to a gradual shift in the conception of linguistic norms: traditional regulatory institutions increasingly see their authority challenged by a significant portion of language users, who formulate normative claims grounded in social arguments. This shift reflects a normativisation process that is now shaped by more participatory and transnational dynamics.
Facial expressions provide critical details about social partners' inner states. We investigated whether event-related potentials (ERP) related to the visual processing of facial expressions are modulated by participants' perceived arousal and valence at the stimulus level. ERPs were recorded while participants (N = 80) categorized the gender of faces expressing fear, anger, happiness, and no emotion. Participants then viewed each face again and rated them on arousal and valence using 1-9 Likert scales. For each participant, ratings of each unique face were linked back to corresponding ERP trials. ERPs were analyzed at all time points and electrodes using hierarchical mass univariate statistics. Three different ANOVA models were employed: the original emotion model, and models with valence or arousal ratings as trial-level regressors. Results from models with ratings highly overlapped with the original model, although they were more temporally restricted. The N170 component was the most impacted by arousal and valence ratings, with four out of six emotion contrasts revealing significant valence or arousal interactions. Emotion effects on the P2 component were mostly unrelated to ratings. On the EPN component, only two contrasts related to both arousal and valence ratings. Thus, ERP emotion effects are related to participants' perceived arousal and valence of the stimuli, although this association depends on the contrast analyzed. These findings, their limitations, and generalizability are discussed in reference to existing theories and literature.
This article is dedicated to the analysis of the phenomenon of language play used in the names of Telegram channels and podcasts specializing in the true crime genre. The relevance of the study is due to the rapid growth in popularity of this genre and the increasing competition for audience attention, which stimulates content creators to use creative and memorable titles. The aim of the research is to identify the main types and functions of language play in names, which implies the systematization of the techniques used and determining their role in attracting audiences and shaping a specific image of the content. The article discusses the theoretical foundations of language play, emphasizing the understanding of language play as a conscious violation of linguistic norms aimed at creating an expressive, comic, or other stylistic effect. Special attention is paid to defining language play as linguistic creative thinking, based on breaking associative stereotypes and requiring active interpretation from the recipient. The choice of research methods (method of complete sampling, descriptive method, method of linguistic and contextual analysis) is determined by the aim of a comprehensive analysis of language play in the names of true crime Telegram channels and podcasts, including the identification, systematization, and interpretation of linguistic features, as well as determining their functional role. The novelty of the work lies in the comprehensive analysis of language play specifically in the context of the names of true crime Telegram channels and podcasts, which has not yet been the subject of close linguistic study. Preliminary results indicate a wide use of techniques such as allusions, metaphors, contrasts, and puns. Their role in creating a unique image, attracting attention, establishing a connection with the audience, and setting the tone for the narrative is analyzed. The genre of "true crime" represents a relatively new area for scientific research, opening up wide prospects for interdisciplinary analysis from literary, linguistic, cultural, psychological, and other perspectives. Further research may also focus on comparative analysis of language play in the titles of true crime content in different languages and cultural contexts.
OBJECTIVE: The term "active larynx" is a nonspecific and subjective term used by otolaryngologists to describe laryngeal inflammation that can influence the timing of airway reconstruction. We sought to measure the reliability of visual assessments of laryngeal inflammation for later scale development. STUDY DESIGN: A cross-sectional study. SETTING: Pediatric tertiary care center. METHODS: We created an image library from a direct laryngoscopy and bronchoscopy database. Blinded judges were asked to rate the characteristics of laryngeal inflammation (edema, erythema, cobblestoned appearance, and ventricular eversion; 5-point Likert scale), the overall "activeness" of the larynx (10-point scale), and whether laryngeal inflammation would influence a delay in reconstructive surgery (yes/no). A tentative scale was also constructed. Intraclass correlations with 2-way random effects, and Fleiss's κ were used to evaluate interrater reliability. The convergent and discriminant validity of the tentative scale were measured. RESULTS: Three pediatric otolaryngologists reviewed 15 larynges for a total of 45 image ratings. Intraclass coefficients indicated substantial agreement for edema (0.76) and erythema (0.83) and moderate agreement for ventricular eversion (0.58). Cobblestoning had low agreement (intraclass correlation coefficient [ICC] < 0.20). The agreement was substantial for overall "activeness" (ICC 0.76) and moderate for whether inflammation would delay surgery (ICC 0.47). By Fleiss's κ, edema and erythema had moderate agreement (0.50 and 0.61, respectively), whereas all others had poor agreement. The convergent and discriminant validity of the tentative scale were reassuring. CONCLUSION: While the reliability of laryngeal inflammation by visual assessment is variable, the creation of an active larynx scale appears feasible.
Pragmatic competence involves understanding and applying sociocultural norms in communication, which is essential for effective language use. Despite grammatical and lexical proficiency, Libyan EFL learners often face challenges in real-life communication due to limited exposure to pragmatic language use, as English functions as a foreign language in Libya. Textbooks serve as key sources of pragmatic input, yet prior research has largely focused on secondary-level materials, overlooking preparatory textbooks. This study investigates the representation of speech acts and language functions in Libyan public preparatory English textbooks for Grades 7, 8, and 9, comprising three coursebooks and three workbooks. All dialogues from these textbooks were transcribed and compiled to reflect a range of communicative contexts and linguistic structures. Drawing on Searle’s (1976) speech act theory and Halliday’s (1978) language function theory, a mixed-methods approach was used. Quantitative data were obtained through systematic content analysis and analysed using SPSS, followed by qualitative interpretation. Findings showed a disproportionate emphasis on representative and directive speech acts, with minimal use of expressive and commissive acts and a complete absence of declarative acts. Similarly, language functions were largely limited to representational and personal uses, while instrumental, imaginative, and regulatory functions were scarcely represented. These imbalances may hinder the development of learners’ pragmatic competence. The study highlights the need for curricular reform and professional development to support the integration of a broader range of pragmatic elements. It emphasizes aligning textbook content with real-world communicative demands to better equip Libyan students for effective language use.
Number of images in each category of the dataset along with their average valence and arousal ratings provided by human participants. The table also illustrates the distribution of human ratings for valence and arousal using the Likert scale.
Human–human interaction studies have shown that live performances of dynamic emotional facial expressions, compared to pre-recorded videos, enhance emotion contagion and spontaneous facial mimicry. While robotic emotional facial expressions can also induce emotion contagion and facial mimicry, the statistical significance of the live presence effect has not been demonstrated. This study utilized a live image relay system to deliver real-time performances of positive (smiling) and negative (frowning) facial expressions by the android Nikola to participants, alongside prerecorded video presentations. Subjective valence and arousal ratings were collected, along with facial electromyography (EMG) from the corrugator supercilii and zygomaticus major muscles. Results indicated that live negative facial expressions elicited lower valence and higher arousal compared to their video counterparts. Facial EMG revealed that live facial expressions induced greater congruent facial muscular activity than pre-recorded videos. These findings suggest that the robotic live presence may enhance affective engagement in socially interactive contexts.
Este trabalho apresenta a compilação, a adaptação ortográfica e a anotação morfossintática da variante do nheengatu falada na região do rio Solimões no século XIX. O nheengatu, única língua viva descendente do tupi antigo, assim como muitas línguas minoritárias, não dispunha de corpora anotados sintaticamente até 2022, ano em que foi lançado o treebank UD_NheengatuCompLin na coleção Universal Dependencies (UD). As etapas aqui descritas indicam a expansão desse treebank, contribuindo para o fortalecimento dos recursos disponíveis para a descrição linguística e o processamento computacional do nheengatu.
Abstract Combining research in developmental sociolinguistics and L1 acquisition, this study explores how caregivers may orient children towards (socio)linguistic norms through parental feedback. Based on self-recorded family interactions in the Belgian-Dutch setting, it applies a top-down quantitative perspective to examine feedback on non-conventional versus non-standard language use, alongside a bottom-up qualitative perspective highlighting factors that influence parental feedback occurrence. Findings reveal limited feedback on children’s non-standard language use, with participation frameworks and multiactivity contexts emerging as possible constraints. The combined approach also foregrounds possible tensions between researcher categorisations and participants’ perspectives. Overall, this study offers a first step in bridging research on parental feedback and sociolinguistic variation, identifying patterns that merit further investigation.
This article describes the Extended Quranic Treebank (EQTB), a comprehensive, multi-layered, and computationally accessible linguistic resource for Classical Arabic (CA), meticulously developed to overcome the documented limitations of the original Quranic Treebank. Leveraging foundational data from established Quranic digital resources, EQTB features systematically expanded orthographic representations generated via algorithmic processing and validation; rigorously refined morphological annotations based on expanded expert-informed schemas, automated re-annotation, and manual curation; and critically, a novel, complete syntactic layer constructed through algorithmic conversion of prior graphical data, Deep Learning-based parsing achieving full coverage under a hybrid constituency-dependency framework, and expert validation. Encompassing the entire Quran (∼132,736 tokens), the dataset is structured in an adapted CoNLL-X format across 43 columns, detailing multiple orthographies, fine-grained morphology (45 tags), and complete hybrid syntax (140 tags/labels), complemented by auxiliary lexicons and schemas. EQTB offers significant reuse potential, providing crucial training/evaluation data for diverse CA NLP tasks (parsing, morphology, diacritization), supporting linguistic research, and enabling the development of advanced pedagogical tools and language technologies.
Analysis code and data for "Asymmetric admixture decouples gene–language coevolution in Eastern Eurasia" This repository contains all computational code and the TyDEE (Typological Dataset of Eastern Eurasia) linguistic database used in our study examining gene-language relationships across Eastern Eurasia. The dataset comprises 541 language varieties across 10 major language families, paired with genome-wide genetic data from 135 populations.
The aim of the study is to identify the functional features of generational neologisms in English as factors of cognitive and social polarization both between and within generations. The article examines the phenomenon of lexemes marked by cohort affiliation and traces their role in shaping symbolic boundaries and intergenerational opposition in English-language discourse. The semantic and pragmatic characteristics of such units are revealed, and their dichotomizing function in communication is substantiated. The scientific novelty of the research lies in identifying and describing cognitive and discursive mechanisms of generational lexical polarization, manifested in the functioning of neologisms with a pronounced cohort affiliation. The novelty also consists in developing and applying the author’s dynamic conceptual modeling scheme, which makes it possible to reconstruct the transformational trajectory of conflictogenic lexemes from primary affiliation to ambivalent functioning and stable contradiction of cognitive attitudes. In addition, the pragmatic status of such neologisms as instruments of cohort self-identification, symbolic differentiation, and reinterpretation of sociocultural norms is clarified, which expands our understanding of the polarization potential of lexical innovations in English-language discourse. As a result, key cognitive features of conflictogenic generational neologisms, their semantic and pragmatic transformations, as well as the discursive scenarios in which they are actualized, have been identified.
OBJECTIVES: If task-irrelevant sounds are present when someone is actively listening to speech, the irrelevant sounds can cause distraction, reducing word recognition performance and increasing listening effort. In some previous investigations into auditory distraction, the task-irrelevant stimuli were non-speech sounds (e.g., laughter, animal sounds, music), which are known to elicit a variety of emotional responses. Variations in the emotional response to a task-irrelevant sound could influence the distraction effect. The goal of this study was to examine the relationship between the arousal (exciting versus calming) or valence (positive versus negative) of task-irrelevant auditory stimuli and auditory distraction. Using non-speech sounds that have been used previously in a distraction task, we sought to determine whether stimulus characteristics of arousal or valence affected word recognition or verbal response times (which serve as a measure of behavioral listening effort). We anticipated that the perceived arousal and valence of task-irrelevant stimuli would be related to distraction from target stimuli. DESIGN: In an online listening task, 19 young adult listeners rated the valence and arousal of non-speech sounds, which previously served as task-irrelevant stimuli in studies of auditory distraction. Word recognition and verbal response time data from these previous studies were reanalyzed using the present data to evaluate the effect of valence or arousal stimulus category on the distraction effect in quiet and in noise. In addition, correlation analyses were conducted between ratings of valence, ratings of arousal, word recognition performance, and verbal response times. RESULTS: The presence of task-irrelevant stimuli affected word recognition performance. This effect was observed generally in quiet and for stimuli rated as exciting (in noise) or calming (in quiet). The presence of task-irrelevant stimuli also affected reaction times. Background noise increased verbal response times by approximately 35 msec. In addition, all task-irrelevant stimuli, regardless of valence or arousal category, increased verbal response times by more than 200 msec relative to the condition with no task-irrelevant stimuli. Valenced stimuli caused the largest distraction effect on response times; there was no difference in the distraction effect on verbal response times based on the stimulus arousal category. Correlation analyses between valence ratings and dependent variables (word recognition and reaction time) revealed that, in quiet, there was a weak, but statistically significant, relationship between valence ratings (absolute deviation from neutral) and word recognition scores; the more valenced a stimulus, the more distracting it was in terms of word recognition performance. This significant relationship between valence and word recognition was not evident when participants completed the speech task in noise. There was no relationship between stimulus ratings (arousal or valence) and reaction time in quiet or in noise. CONCLUSIONS: Valenced (positive and negative) or exciting task-irrelevant non-speech sounds can negatively affect word recognition and increase listening effort. Future study should consider the emotional content of task-irrelevant stimuli when evaluating potential distraction effects.
We provide an overview of the Universal Dependencies multilingual corpus collection, its current status and numerous extensions, such as the UNER annotation of named entities or the CorefUD annotation of coreference and anaphora. We discuss the utility of the data in several areas of Digital Humanities, with a particular focus on comparative linguistics and typology.Keywords: annotated corpus; treebank; morphology; syntax; typology.
French is often celebrated for its clarity and precision – a legacy shaped by Cartesian rationalism and prescriptive language policies. However, the evolving forms of spoken French challenge this ideal of fixed linguistic norms. This study examines one such feature: the right-peripheral duplication of the subject pronoun je with its tonic counterpart moi, a recurrent but underexplored phenomenon in spoken French. The primary objective is to understand how this syntactic feature functions pragmatically and emotionally in real-life discourse. Using a corpus of movie dialogues, the analysis shows that duplication plays a role in managing conversational flow, expressing personal stance, and enabling self-repair. Through a multidisciplinary lens that draws from sociolinguistics, pragmatics, and applied linguistics, the study argues that such variation enriches the expressive potential of French and complicates the rigid divide between written norms and spoken practice. It also suggests that incorporating these features into language pedagogy can support a more inclusive, realistic understanding of French as a living language.
The International Affective Picture System (IAPS) is widely used in emotion and attention research but was originally validated in North America. Because cultural factors can shape emotional responses, cross-cultural validation is necessary before applying IAPS in new contexts. This study presents the first systematic validation of IAPS for the Malaysian population. A total of 142 undergraduates rated 60 IAPS images on valence, arousal, and dominance. Ratings showed high internal consistency and strong positive correlations with U.S. norms. However, Malaysians reported significantly higher arousal for the selected images, suggesting a sociocultural influence on affective appraisal. Affective space analysis revealed the typical boomerang-shaped distribution with a negativity bias. No significant gender differences were observed. These results support the use of IAPS in Malaysia while highlighting the need to account for cultural variations, particularly in arousal, when selecting stimuli for cross-cultural emotion research.
The POS tagging task is a sequence tagging task, where the goal is to predict the correct part-of-speech for each token in a sentence. For training data, we use the Gimpel dataset from [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0323064#pone.0323064.ref022" target="_blank">22</a>] with the crowd-sourced labels provided by [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0323064#pone.0323064.ref023" target="_blank">23</a>] mapped to the universal POS tag set in [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0323064#pone.0323064.ref024" target="_blank">24</a>]. The dataset consists of 1000 tweets (17,503 tokens) labeled with Universal POS tags and annotated by 177 annotators. Each token received at least 5 annotations. The IAA is 0.725 and the average annotator accuracy with respect to the gold labels is 67.81%. We use the publicly available sample of the Penn Treebank POS dataset [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0323064#pone.0323064.ref025" target="_blank">25</a>] accessed from NLTK [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0323064#pone.0323064.ref026" target="_blank">26</a>] as our out-of-domain test set, which consists of 3,914 sentences from Wall Street Journal articles (100,676 tokens). Distribution shift on this task is based on the data distribution (source: tweets, target: news). (PDF)
Grapheme-to-phoneme (G2P) conversion for Persian presents unique challenges due to its complex phonological features, particularly homographs and Ezafe, which exist in formal and informal language contexts. This paper introduces an intermediate language specifically designed for Persian language processing that addresses these challenges through a multi-faceted approach. Our methodology combines two key components: Large Language Model (LLM) prompting techniques and a specialized sequence-to-sequence machine transliteration architecture. We developed and implemented a systematic approach for constructing a comprehensive lexical database for homographs with multiple pronunciations disambiguation often termed polyphones, utilizing formal concept analysis for semantic differentiation. We train our model using two distinct datasets: the LLM-generated dataset for formal and informal Persian and the B-Plus podcasts for informal language variants. The experimental results demonstrate superior performance compared to existing state-of-the-art approaches, particularly in handling the complexities of Persian phoneme conversion. Our model significantly improves Phoneme Error Rate (PER) metrics, establishing a new benchmark for Persian G2P conversion accuracy. This work contributes to the growing research in low-resource language processing and provides a robust solution for Persian text-to-speech systems and demonstrating its applicability beyond Persian. Specifically, the approach can extend to languages with rich homographic phenomena such as Chinese and Arabic
Understanding the nuances in everyday language is pivotal for advancements in computational linguistics & emotions research. Traditional lexicon-based tools such as LIWC and Pattern have long served as foundational instruments in this domain. LIWC is the most extensively validated word count based text analysis tool in the social sciences and Pattern is an open source Python library offering functionalities for NLP. However, everyday language is inherently spontaneous, richly expressive, & deeply context dependent. To explore the capabilities of LLMs in capturing the valences of daily narratives in Flemish, we first conducted a study involving approximately 25,000 textual responses from 102 Dutch-speaking participants. Each participant provided narratives prompted by the question, "What is happening right now and how do you feel about it?", accompanied by self-assessed valence ratings on a continuous scale from -50 to +50. We then assessed the performance of three Dutch-specific LLMs in predicting these valence scores, and compared their outputs to those generated by LIWC and Pattern. Our findings indicate that, despite advancements in LLM architectures, these Dutch tuned models currently fall short in accurately capturing the emotional valence present in spontaneous, real-world narratives. This study underscores the imperative for developing culturally and linguistically tailored models/tools that can adeptly handle the complexities of natural language use. Enhancing automated valence analysis is not only pivotal for advancing computational methodologies but also holds significant promise for psychological research with ecologically valid insights into human daily experiences. We advocate for increased efforts in creating comprehensive datasets & finetuning LLMs for low-resource languages like Flemish, aiming to bridge the gap between computational linguistics & emotion research.
This article offers a comparative analysis of language use in Uzbek and English mass media, specifically examining newspaper articles and online news. By employing both quantitative and qualitative research methods, the study investigates how linguistic features such as syntax, lexical choice, and rhetorical structures differ in Uzbek and English news discourse. The research focuses on the ways in which cultural and societal norms shape the presentation of information, the frequency of borrowed terms, and the general stylistic differences that arise when conveying similar content. It was found that Uzbek mass media, influenced by a rich cultural heritage and recent linguistic reforms, rely on more culturally embedded phrases, while English mass media demonstrate frequent use of modern jargon and direct expression of opinions. These differences in language use reflect each society’s broader ideologies regarding news sharing and public discourse, ultimately providing deeper insight into how journalists and news agencies communicate with their audiences.
The article examines the Jadid legacy at the center of drama and analyzes the impact of the reform movement (religious, cultural, educational, and political directions) on literary language. The connection of Jadid dramaturgy with the traditions of stage and folk theater, its role in raising social issues, and the enrichment of theater lexicon with units carrying the semantics of modernization are shown. To systematize the lexical layer in the work, a corpus-based dictionary program consisting of explanatory, etymological, thematic, ethnographic, paremiological, and author's dictionaries is proposed. As a result, Jadid plays are evaluated as a “living document” of the language of the period and are based on the reconstruction of the history of the language and the enrichment of modern norms as a reference source.
There are limited discussions on how translanguaging practices may be tailored according to needs and contexts by providing examples of the implementation of translanguaging in different countries. Thus, this chapter reports on implementing translanguaging premises and pedagogies in light of critical needs analysis to compare and offer practical recommendations. Türkiye (at a state university where medical English was delivered using CLIL), Brazil (at a state university where linguists and computer scientists develop annotated treebanks of diverse dialects to be used in Natural Language Processing applications, among them a language used by the Warao refugees in Brazil, emerging from the contact between the Warao language, Venezuelan Spanish, and Brazilian Portuguese). Here, the target situation is a site for possible transformation and a translanguaging approach allows. To the knowledge of this chapter's authors, this study in two different contexts is the first of its kind on translanguaging.
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.
Background and objective Navigating interprofessional team dynamics is essential for high-quality patient care in pediatric settings. This study involved medical students on a pediatric clerkship who explored the characteristics of high- and low-performing clinical teams by considering drivers and barriers to effective team performance. By analyzing these reflections, the study aimed to identify key facilitators and barriers to effective team-based care. Methods Survey evaluations and narrative reflections were completed by third-year students (M3s) at a single US allopathic medical school during their pediatric clerkship after receiving training in TeamSTEPPS® and Institute for Healthcare Improvement (IHI) Open School, two programs that support quality improvement (QI) in healthcare. Descriptive statistical and inductive thematic analyses were conducted on the resulting 183 narratives. A valence rating system was employed to quantify narrative responses as positive/attractive or negative/aversive, with a Cronbach alpha of 0.958 between two independent reviewers. Results Inductive thematic analysis generated 40 themes that we grouped under the five TeamSTEPPS® skill domains (situation monitoring, communication, leadership, team structure, mutual support) into thematic conceptual models. High-performing teams demonstrated open communication, role clarity, shared understanding, and organized task delegation. Low-performing teams displayed a lack of information exchange, uncertain team roles, unhealthy power dynamics, and disorganized task delegation. Conclusions After instruction in QI methods, pediatric clerkship students identified consistent drivers of and barriers to effective team performance. The themes within the narrative reflections can provide insights into improving patient care delivery, specifically around situation monitoring, communication, and team structure.
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
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.
Modern trends in digital communication exacerbate the problem of changing language norms under the influence of social networks, making the investigation of this issue particularly relevant. The purpose of the preset study was to identify and analyse transformations in language norms and usage as a result of the active use of social networks as the primary means of everyday communication. The study employed methods of linguistic observation, content analysis, and comparative analysis. The study revealed stable changes in written and oral communication caused by Internet communication: active use of slang, emojis, abbreviations, and Anglicisms; the study recorded an expansion of usage due to norms formed within online communities. The linguistic features of popular platforms (WhatsApp, Instagram, TikTok, Telegram) were analysed, as well as differences in the speech behaviour of users depending on their age and social context. The study found that the norms of online communication often contradict conventional literary norms, thereby influencing the formation of linguistic norms among young people. The data obtained also indicated the development of specific communication strategies driven by technical limitations and the functionality of various platforms, which leads to unique linguistic manifestations in each online community. Furthermore, the analysis revealed that the intensity and nature of language changes directly correlated with the level of user involvement in interactive forms of communication, such as commenting and taking part in discussions. The practical significance of the study lies in the possibility of applying its findings in educational and media teaching practice – in the development of training courses on modern linguistics, media literacy, as well as in the field of editing and translation
This paper examines the vital role context plays in Interactional Sociolinguistics (IS) especially as it relates to cross-cultural miscommunications exemplified in British/American and Nigerian data. This study, therefore, critically investigates the intricate dynamics of how context shapes interactional communication, highlighting how cross-cultural differences, linguistic norms and societal expectations and contextualization cues often lead to semantic misrepresentation, misunderstandings and miscommunications. Drawing on empirical data from complex and linguistically diverse cultural background, the study demonstrates how Gumperz IS and contextualization theories can lighten-up the complex interplay between language, culture and context in cross-cultural sociolinguistic interactions. The study drew from purposively selected structured interviews involving electricians, bricklayers, teacher/pupils exchange and Head of Department/staff conversations, which were subjected to discourse analysis. The data reflect work environment across different regions, including USA, UK and Nigeria. The findings reveal that language is consequential in sociocultural context in which communication takes place, and also brings to the fore that effective cross-cultural communication requires not only linguistic competence but also a deep understanding of the cultural nuances and contextual factors that shape interactional dynamics. This paper also contributes to the unburdening of age-long perception that pragmatic context alone rather than cross-cultural differences often lead to miscommunication and distortion of intended meaning in interactional communication in an increasingly globalized world. Keywords: Interactional Sociolinguistics, Cross-Cultural Miscommunication, Contextualization Cues, Context, Cultural Differences.