Papers reviewed and determined not to be word norm studies. Use the flag icon to report errors or suggest re-inclusion.
18265 papers
In the 20th century, the concept of “compliance” gained prominence in academic publications, particularly within the realms of medical and financial-economic discourse. Recently, its application has extended to fields such as pedagogy, psychology, and philology. This concept encompasses two primary substantive dimensions: the first involves the establishment of requirements aligned with existing norms and standards, while the second pertains to the genuine and conscientious adherence to these stipulations. Contemporary sociological studies are beginning to explore the willingness of certain religious adherents to fulfill tax obligations, necessitating a theoretical framework for understanding these practices within the context of academic religious studies. Historically, the term “compliance” — denoting agreement, indulgence, voluntary concession, and self-restraint — originated in English from Latin ecclesiastical terminology. It encapsulated specific norms governing interreligious and interfaith relations that evolved within Christian culture, particularly during the Reformation, a period marked by significant conflict. The imperative to achieve consensus with dissenters for the collective civil good prompted the formulation of new legal and literary standards, addressing challenges such as the transformation of various “religion names” and “confessional names,” wherein derogatory connotations were supplanted by neutral or respectfully affirming alternatives. This analysis draws upon resources from dictionaries, encyclopedias, the linguistic database “National Corpus of the Russian Language,” and additional scholarly sources.
Zora Neale Hurston’s Their Eyes Were Watching God presents a radical departure from the tragic mulatta trope in African American literature by centering a black feminist protagonist, Janie Crawford, who is neither defined by racial ambiguity nor constrained by the moral expectations imposed on middle-class black women of the 19th and early 20th centuries. Unlike her literary predecessors, Janie speaks in black vernacular, embraces her sexuality, and ultimately finds agency outside of marriage, despite the novel’s exploration of love and relationships. This paper argues that Hurston’s portrayal of Janie’s three marriages illustrates a pessimistic view of black women’s status within love and marriage, revealing that even true love cannot fully liberate them from patriarchal constraints. Through an analysis of Janie’s relationships, this paper demonstrates how Their Eyes Were Watching God challenges intra-community sexism and critiques the internalization of white patriarchal values by black men. Additionally, it explores Hurston’s literary innovations, particularly her use of black dialect and folklore, as an intervention against white literary standards and a foundation for later black feminist narratives. Hurston’s use of black dialect and folklore functions not merely as a literary gesture, but as a deliberate political and aesthetic intervention. The black vernacular, often seen as non-literary or even “primitive” in dominant white and even black literary standards, becomes in Hurston’s hands a medium of authenticity, resistance, and empowerment. By embedding Janie’s voice within this dialect—particularly through her dialogues with other women and her defiance of male authority—Hurston decentralizes white linguistic norms and reclaims black southern oral traditions as legitimate literary forms.By foregrounding the singularity of Janie’s experience, Hurston’s novel marks a turning point in the representation of black women in literature, paving the way for subsequent authors like Alice Walker and Toni Morrison to further explore Black female autonomy and agency.
Large language models (LLMs) have materially changed natural language processing (NLP).While LLMs have shifted focus from traditional semantic-based resources, structured linguistic databases such as WordNet remain essential for precise knowledge retrieval, decision making and aiding LLM development.WordNet organizes concepts through synonym sets (synsets) and semantic links but suffers from inconsistencies, including redundant or erroneous relations.This paper investigates an approach using LLMs to aid the refinement of structured language resources, specifically WordNet, by an automation for multiple hypernymy resolution, leveraging the LLMs semantic knowledge to produce tools for aiding and evaluating manual resource improvement.
Sanskrit is traditionally described as a free-word-order language, and the indigenous grammatical tradition explains what constrains word combination through three notions: ākāṅkṣā (syntactic expectancy), yogyatā (semantic compatibility), and sannidhi (proximity or contiguity). This study asks whether sannidhi, read as a locality constraint, is empirically supported, and how it relates to the cross-linguistic principle of dependency-length minimization (DLM). Using the Universal Dependencies Treebank of Vedic Sanskrit (27,182 sentences; 206,440 tokens), I compared observed dependency lengths against a random-projective baseline and a minimal-arrangement heuristic, partitioned arcs by grammatical relation, quantified non-projectivity, and traced variation across the corpus's chronological layers. At the whole-sentence level, Vedic showed no dependency-length minimization beyond the projectivity constraint: observed mean length (1.996) was statistically indistinguishable from the random-projective baseline (2.002) and far above the minimal arrangement (1.512). This near-parity, however, masked a systematic relation-specific split. Core verb-argument relations—the kāraka-type expectancy relations—were placed reliably closer than their own random baseline (mean deviation −0.36 tokens, 95% CI [−0.38, −0.34]), whereas coordinate, appositional, and modifier relations were placed at or beyond chance distance (+0.16 tokens, 95% CI [+0.13, +0.18]). Non-projectivity was common (19.4% of sentences) but overwhelmingly mild and well-nested, and it declined sharply from the Ṛgvedic layer (35.9%) to the Sūtra layer (11.0%). An independent classical treebank reproduced both the aggregate parity and the non-projectivity rate. I argue that sannidhi is best understood not as global length optimization but as a selective, expectancy-scoped locality operating over ākāṅkṣā-linked pairs, and that Vedic word order becomes measurably more projective over time.
Abstract The paper introduces Parallel Trees, a novel multilingual treebank collection that includes 20 treebanks for 10 languages. The distinguishing property of this resource is that the sentences of each language are annotated using two syntactic representation paradigms (SRPs), respectively based on the notions of dependency and constituency. By aligning the annotations of existing resources, Parallel Trees represents an example of exploiting pre-existing treebanks to adapt them to novel applications. To illustrate its potential, we present a case study where the resource is employed as a benchmark to investigate whether and how BERT, one of the first prominent neural language models (NLMs), is sensitive to the dependency- and constituency-based approaches for representing the syntactic structure of a sentence. The case study results indicate that the model’s sensitivity fluctuates across languages and experimental settings. The unique nature of the Parallel Trees resource creates the prerequisites for innovative studies comparing dependency and phrase-structure trees, allowing for more focused investigations without the interference of lexical variation.
This article examines the methodological aspects of using the National Corpus of the Kazakh language in school-based Kazakh language lessons and analyzes its theoretical and practical significance. The study demonstrates the effectiveness of the national corpus in developing students’ communicative skills—namely, reading, speaking, listening, and writing—and in forming linguistic norms. It was identified that the corpus provides natural language data, enabling students to understand word meanings through text structure, observe the functions of grammatical forms, and distinguish stylistic and communicative features of speech. In addition, corpus materials help students master the structure of dialogue, use words accurately, and understand phraseological units. Regarding linguistic orientation, the corpus fosters learners’ research skills by enhancing their ability to independently identify language patterns, compare linguistic phenomena, and draw conclusions. The findings of the study show that the national corpus is an important tool for improving linguistic competence, developing speech culture, and strengthening research skills. The article focuses on two main directions—developing communicative skills and forming linguistic norms through the use of the corpus. The results confirm that systematic use of the national corpus significantly enhances students’ linguistic competence, speech culture, and research abilities.
Just as kindness is prioritized in mate selection, warmth and fairness are often favored in cooperative social interactions, sometimes over competence and wealth, suggesting that these traits may influence social status. We conducted three studies to examine how heterosexual men (N = 193) and women (N = 178) from the U.S. evaluate men's faces for mating- and status-relevant traits, both alone and in combination with vignettes describing their economic resources and ethical reputation. The vignettes presented all men as generally smart, nurturant, and healthy, but pitted economic resources against ethical reputation surrounding care and fairness. Study 1, pitting men's ethics against their resources, found that an ethical reputation enhanced ratings of long-term mating attractiveness, prestige, intelligence, and kindness, but short-term mating attractiveness and physical dominance ratings were unaffected. Study 2, pitting men's parent's ethics against parental resources, yielded results consistent with Study 1. Study 3, pitting men's ethical history related to their adolescence with their current resources, found similar results to studies 1 and 2 with one key difference: women lowered prestige ratings for men with an unethical past, and men lowered physical dominance ratings for these men. The discussion reassesses notions of status and resources, exploring their relative significance in mating evaluations.
<ns3:p>Feminatives, defined in this article as feminine forms of job titles, roles, and functions, sparksignificant controversy in Poland, being a focal point of debates on gender equality and linguisticinclusivity. An analysis of a survey conducted among 662 respondents reveals diverseattitudes toward feminatives, influenced by gender, age, education, and place of residence.The study underscores the role of feminatives in evolving social and linguistic norms andindicates the need for further research into their function in the Polish language.</ns3:p>
This article explores the role of five expressive punctuation marks – multiple exclamation marks (!!!), exclamation mark (!), full stop (.), ellipsis (...), and null punctuation (ø) – as cues to writer attitudes in CMC. Specifically, it investigates how the underlying meaning of expressive punctuation influences the perceived emotional valence of discourse referents within exclamative constructions. In a 1x5 between-subjects repeated measures design, valence ratings were collected for 120 discourse referents embedded in exclamative constructions manipulated by message finale punctuation mark (e. g., What a view!!!/!/./…/ø) on a 1 (negative) to 9 (positive) scale. For inherently positive discourse referents, a clear positivity hierarchy in the overall valence of embedded discourse referents emerges, indicating a differential influence of punctuation on perceived valence: multiple exclamation marks > exclamation marks > null punctuation > full stop > ellipsis. For inherently negative discourse referents, the differences between the conditions are less distinct. Notably, only multiple exclamation marks yield a significantly lower valence rating within that range of values. While the findings for inherently positive referents align with prior assumptions on the expressive meaning of different punctuation marks in CMC, the observed pattern for inherently negative referents cannot be readily explained by existing literature on expressive punctuation in CMC.
This study adapts the Affective Norms for English Words (ANEW) dataset for Mexican Spanish, validating emotional dimensions in culturally relevant contexts. A total of 753 participants rated 1,028 translated words on valence, arousal, and dominance using the Self-Assessment Manikin (SAM) scale. The adaptation ensured linguistic equivalence through iterative translation and consensus processes, selecting region-specific terms verified with the Corpus XXI of the Royal Spanish Academy. Split-half correlations confirmed high internal consistency across dimensions, demonstrating stable and reliable ratings within the Mexican sample. Cross-linguistic analyses revealed strong correlations between Mexican Spanish and norms for European Portuguese and Spanish, with moderate correlations to English norms, highlighting cultural and linguistic influences on emotional word ratings. Gender differences further provided insights into demographic factors affecting emotional word processing. These findings underscore the need for culturally specific adaptations in research, ensuring that affective norms align with regional language use and emotional perception. This study offers a methodological framework applicable to other linguistic and cultural contexts, enhancing the precision of cross-cultural research in affective science.
Abstract This study examines the usage, semantics, and affective valence of olfactory metaphors in English, addressing a gap in sensory language and metaphor research. We analyze eight basic smell lexemes ( smell, aroma, scent, odor, stench, stink, reek, fragrance ) in the iWeb corpus, tracing their abstract noun collocates through frequency counts, WordNet hypernym paths, intersection analysis, and affective valence ratings. Our results reveal that English olfactory metaphors are highly productive, mapping smell perception onto a broad array of abstract experiences, especially socioemotional and moral domains. The eight patterns exhibit pronounced affective polarization: while some (e.g., fragrance, aroma ) skew positive, most (e.g., stink, stench, reek, odor ) skew negative, reflecting both olfactory hedonics and a cognitive negativity bias. These findings deepen our understanding of how sensory language structures abstract thought and affirm the rich figurative potential of smell in English, with implications for theories of sensory language, conceptual metaphor, and embodied cognition.
This is an accepted article with a DOI pre-assigned that is not yet published.The purpose of this paper is to test the correlation between V2 word order and its presumed micro-cues. Micro-cues are structural manifestations that have been suggested to associate to a syntactic phenomenon, making its organization and acquisition accessible to users and learners. Three micro-cues of declining Medieval French V2 identified in the literature are tested for their relation using a treebank method. Statistical analyses confirm the expected correlation. The results lend plausibility to a micro-cue model for the acquisition and structuration of syntactic phenomena.
Recent advancements in thermal device technology present new possibilities for conveying sensations and emotions in diverse applications. Yet, systematic investigations into the design parameters of thermal feedback and their effects on elicited sensations and emotions remain underexplored. To address this gap, we created 36 thermal feedback patterns by systematically varying the amplitude of change, rate of change, and indoor temperature, and applied them across three body sites on the hand, forearm, and upper arm. We then collected perceived intensity, valence, and arousal ratings from 12 participants. The results revealed the efficacy of the thermal design parameters. For example, the amplitude of change served as the primary parameter influencing the intensity and arousal ratings across body sites, while it affected valence only when thermal feedback was applied to the forearm and upper arm. Using the collected data, we developed a neural network to predict the intensity sensation and emotion ratings elicited by thermal feedback. Our model outperformed three baseline machine learning models and demonstrated strong alignment with non-linear sensory and emotional responses. We present four guidelines for designing thermal feedback and discuss implications for future research and applications in haptic design.
The article examines the issue of translating idioms in I.S. Turgenev's novel Fathers and Sons in the context of cultural and historical influences on translation decisions. A comparative analysis of three English translations of the novel, produced in the 19th, 20th, and 21st centuries, is conducted to identify changes in the translation of idiomatic expressions. Special attention is given to the concept of «cultural time» as a factor affecting translation strategies. The study demonstrates that each generation of translators adapts the text according to the prevailing cultural and linguistic norms of its time. The analysis highlights how the perception of Russian idioms evolves and how cultural shifts influence the choice of equivalents in the target language. The findings of this research may be valuable for specialists in literary translation and intercultural communication.
The rapid development of Neural Machine Translation (NMT) and Large Language Models (LLMs) marks what can be described as an Algorithmic Turn in translation studies.This shift fundamentally reconfigures translation from a primarily human-centered act of linguistic mediation to a process increasingly shaped by computational systems and algorithmic logic.This paper critically examines the growing influence of Artificial Intelligence on intercultural narratives and on the process of semantic transfer in an interconnected global context.While AI-driven translation technologies offer unprecedented speed, scalability, and accessibility, their widespread adoption also raises significant concerns related to cultural authenticity, linguistic diversity, and the preservation of meaning.Drawing on a critical-theoretical framework, the study argues that AI systems function not merely as neutral tools but as active co-authors in the construction of crosscultural meaning.The analysis focuses on two central issues: first, the ways in which intercultural narratives are shaped by AI models trained on culturally imbalanced datasets, often privileging dominant linguistic norms and contributing to cultural homogenization; and second, the inherent limitations of AI in handling semantic nuance, particularly in relation to irony, implicit power relations, and culturally embedded meanings.The paper ultimately contends that the Algorithmic Turn produces a paradoxical outcome-a translation that is linguistically fluent yet culturally hollow.Addressing this paradox requires moving beyond accuracy metrics toward a critical evaluation of AI's ethical, cultural, and epistemological implications, reaffirming the essential role of the human translator as an intercultural mediator whose expertise complements, rather than competes with, technological innovation.
Colors serve as an important embodied source of perceptual experiences for conceptualizing emotional concepts. This study offers an image-based visual corpus analysis on perceptual (dis)similarities among six basic color terms (black, white, red, green, yellow, blue) and 63 emotion-label words in English. The investigation focuses on two primary questions: (i) whether the six colors are significantly different regarding their contributions in conceptualizing emotional concepts, and (ii) how color-emotion association patterns are shaped by valence and arousal. Empirical analyses were conducted and discussed using the degree of perceptual (dis)similarities between the target color terms and emotion words as an indicator of the strength of color-emotion associations, based on a dataset of 69*100 images collected from Google Image, comprising 63 emotion words and 6 color terms, with 100 images retrieved for each term. The results reveal that (i) significant differences exist among the six colors in their effectiveness at capturing affective (dis)similarities among various emotional concepts, as well as in their association strength with the affective domain, and (ii) the valence and arousal ratings of emotion words are significantly correlated to the strength of their associations with five of the six color terms, with the exception of blue. This study provides an image-based empirical exploration of the cognitive mechanisms responsible for color-emotion mappings, highlighting the essential and distinctive roles of colors in understanding emotional concepts.
Correction: Task-based explanation for genre effects: Evidence from a dependency treebank
This project contains two lexical databases of Italian blends collected using different methods. Both resources have been analysed in my Ph.D. thesis "Un itangliano semplesso. Analisi di due campioni di parole macedonia", and are also the core data of other publications.
Metaphorical mappings play a central role in embodied cognition, with prior research suggesting that power is associated with higher vertical spatial locations. This study investigated whether spatial cues influence gender classification and dominance attributions for androgynous faces that lack inherent gender or power cues. Using a multi-laboratory approach across twelve countries (N = 546), participants categorized gender-ambiguous faces as male or female and rated their dominance after brief exposures (100 msec vs. 500 msec) at different spatial positions. We hypothesized that faces in higher locations would be more frequently classified as male and rated as more dominant, particularly with longer exposure durations. However, results revealed that while exposure duration affected gender classification (longer durations increased the likelihood of male categorizations), spatial positioning had no significant effect on response times or dominance ratings. Instead, dominance ratings were strongly linked to gender classification, with faces categorized as male being rated as more dominant, regardless of spatial positioning. These findings suggest that the power-space metaphor may not operate automatically in social perception without salient contextual cues, while highlighting the persistent influence of implicit gender biases in dominance attribution.
Mental health issues such as depression, stress, anxiety, and personality disorders are increasingly prevalent, particularly within online communities. This study proposes a lightweight and efficient multi-class classification framework to identify five mental health conditions using Reddit user-generated posts. While previous studies predominantly rely on conventional CNNs or standard machine learning techniques for binary classification, our work introduces a novel Bidirectional Long Short-Term Memory (BiLSTM) model integrated with an attention mechanism. The architecture is further enhanced by synonym-based data augmentation using the WordNet lexical database, which improves semantic diversity and enhances model robustness, particularly for underrepresented classes. Unlike prior works that focus narrowly on binary classification or employ transformer-based models with high computational demands, our model offers a lightweight, high-performance architecture optimized for multi-class detection and real-world deployment. Experimental results demonstrate that the proposed model achieves a peak validation accuracy of 95.02%, along with precision 95.08%, recall 95.02%, and F1-scores of 95.03%. These findings support the advancement of efficient AI-driven diagnostic systems in mental health analytics and lay the groundwork for future integration into mobile or resource-constrained platforms.
The primary challenge in studying children's and adolescents' emotional issues lies in reliably and effectively eliciting their emotional states in research settings, a process that is essential for understanding the development and regulation of emotions across childhood and adolescence. Current research in this field predominantly employs situational induction, facial expression paradigms, and audiovisual stimuli as the main approaches to evoke emotional responses in young participants. While these methods have provided valuable insights, a critical limitation of existing pediatric emotion elicitation techniques is their adult-centric design framework, which often fails to fully account for the developmental origins, contextual factors, and age-specific characteristics of children's and adolescents' emotional experiences. In response to this limitation, the present study advocates for a child-centered research approach that explicitly prioritizes the emotional experiences of youth, aiming to enhance ecological validity by designing stimuli that are closely aligned with the everyday social and environmental contexts in which children and adolescents naturally experience emotions. Furthermore, given the current lack of culturally appropriate and developmentally tailored image databases for socio-emotional elicitation in young populations, this research seeks to construct a child-validated image library capable of safely and effectively eliciting emotional responses. The resulting database is intended to provide a reliable experimental platform that can be used to investigate the mechanisms of emotional processing in youth and to support subsequent interventions and programs aimed at promoting emotional health and socio-emotional development. Two empirical studies were conducted to establish and validate the Chinese Child-Adolescent Affective Picture System (CCAAPS). In Study 1, semi-structured interviews with children and adolescents from Shandong and Anhui provinces in China were analyzed using grounded theory to identify principal sources of emotion in daily life. A total of 20 participants, balanced by gender and aged 6–18 years, provided narratives highlighting a range of emotional triggers. Findings revealed that interpersonal interactions—particularly school-based social contexts—constituted the primary emotional triggers. These qualitative insights were systematically coded to extract keywords that guided the selection of images for the database. Study 2 recruited a total of 491 participants, aged between 6 and 18 years. Each participant was asked to evaluate a set of 311 socio-emotional images that had been preselected based on the findings from Study 1. The images were rated along three distinct emotional dimensions—valence, arousal, and motivational intensity—using a revised 5-point Likert scale. Analysis of the subjective ratings revealed statistically significant differences among positive, neutral, and negative images across all three dimensions (p <.001 for all comparisons), demonstrating that the images were capable of eliciting differential emotional responses in a manner consistent with their intended affective categories. Furthermore, the internal consistency of participants’ ratings was assessed using Cronbach’s alpha, yielding coefficients exceeding 0.85 for each dimension. These results indicate that the image ratings were reliable across participants and that the emotional dimensions measured were internally coherent. The CCAAPS has several implications. First, as a standardized tool grounded in children’s real-life experiences, it provides a link between laboratory paradigms and everyday emotional phenomena, supporting research on emotion recognition, affective processing, emotion-related psychopathology (e.g., depression, anxiety), interpersonal regulation, and antisocial behaviors such as bullying. Second, it can be applied in socio-emotional learning (SEL) to provide culturally appropriate materials for empathy training and emotion regulation interventions in educational contexts. Third, by providing a validated, developmentally appropriate, and culturally adapted affective picture system, the CCAAPS enhances methodological infrastructure for developmental affective science in China. In conclusion, the present research contributes both conceptually and practically to the study of youth emotions by constructing the first child-centered, culturally adapted affective picture system for Chinese children and adolescents. The CCAAPS establishes an ecologically valid resources for investigating socio-emotional experiences, enriches the toolkit for researchers. This work therefore provides an essential infrastructure for future studies seeking to understand, support, and promote the emotional health of Chinese youth.
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.
This research introduces a framework for comparative evaluation of human-curated versus AI-generated affective images using a multimodal AI agent. The dataset (N=80 pictures) includes a selection of 40 human-curated images from the Open Affective Standardized Image Set (OASIS), and a set of 40 synthetic images generated specifically for this study. The synthetic dataset was created by prompting the “GPT Image 1” model, a specialized image generation model built on GPT-4o, with the goal to represent four target emotional states—Excitement, Frustration, Boredom, and Relaxation. A custom AI agent was deployed to rate all images along the valence and arousal dimensions of the affective circumplex model. Statistical analyses were performed to compare: (1) human vs agent image ratings for OASIS and (2) the agent’s ratings of the AI-generated image set and OASIS. The findings indicate that the AI agent reliably aligned with the human ratings and that GPT-4o can serve as both a generator and evaluator of affective content, thus supporting scalable, human-free validation pipelines. This approach contributes to the field of affective computing by enabling rapid generation and analysis of emotionevoking stimuli, with potential applications in experimental psychology and mental health.
We present EmoWork, a multimodal, multi-label dataset designed to support emotion and stress detection in realistic interpersonal work settings. Interpersonal work—common in occupations such as customer service—often requires workers to regulate their emotional expressions in response to strong affective stimuli. These demands, shaped by organizational display rules, present a unique challenge for affective computing systems, particularly in scenarios where internal emotional states diverge from observable behaviors.Despite this, no public datasets exist that capture such dynamics of affect in naturalistic settings. To address this gap, we collected physiological, behavioral, and self-reported data from call center workers who engaged in role-play scenarios simulating customer service interactions with professional actors portraying dissatisfied customers. The dataset includes self-reported affective ratings, which are used as labels for classification, synchronized recordings from three wearable devices (i.e., Polar H10, Empatica E4, and Muse S), and features extracted from video and audio data. The EmoWork dataset advances affective computing by offering context-rich, multimodal data grounded in realistic interpersonal work scenarios.
The article examines the structure and functionality of the Machine fund of the Bashkir language (MFBL), which was established at the Institute of History, Language and Literature of the UFIC RAS. The MFBL is an integrated system designed to search for linguistic information. It includes several databases. Work on the creation of the MFBL began in 2006. At the moment, the fund consists of ten major sections: general dictionary; lexicographic databases; grammatical bases; experimental phonetic bases; catalogues of handwritten and old printed books; dialectological base; corpus databases containing texts of prose, journalistic, and folklore works in the Bashkir language. In total, the fund contains 75 different linguistic databases. The MFBL system was developed based on the ORACLE database management system. The inclusion of linguistic data in a relational database requires careful analysis and separation of information into its component parts, which makes it possible to efficiently and quickly obtain generalized characteristics. The machine fund of the language has not only scientific, but also practical significance. It is a tool for optimizing and improving the quality of educational materials, including the preparation of language examples for textbooks and teaching aids. The Ministry of Education of the Republic of Bashkortostan actively promotes the use of the Machine Fund among teachers of the Bashkir language. The use of Machine Resources by editors, journalists, and translators certainly contributes to improving the level of Bashkir language proficiency. The machine fund of the language also has significant socio-economic value. Due to the fact that a large number of dictionary and grammar materials are available on the Internet, there is no need for the expensive process of republishing and distributing these materials on paper; Automatic search in the foundation’s databases makes it possible to find philological information faster. This, in turn, accelerates the creation of new linguistic developments and didactic materials. Due to the availability of Bashkir language material on the Internet, residents of the republic can be satisfied with the current language and national policy.
The gambling landscape is constantly evolving. Digital technologies feature several emerging forms of gambling-like activities (‘gamblification’) including free-to-play social casino games and video game loot boxes, as well as the opportunity to spectate gambling on streaming platforms such as Twitch, Kick and YouTube (Macey & Hamari, 2024). Recent research has begun to characterize links between these activities and real-money gambling. For example, young adults who purchase loot boxes show an increased likelihood of initiating gambling over the next 6 months (Brooks & Clark, 2023). We do not yet understand how early exposure to randomized rewards in these settings draws people to gambling, and the factors associated with risk and resilience to gambling harm. This study will focus on gambling streams, as a popular medium through which young people are exposed to gambling content. Watching a gambling stream does not involve betting or winning money, but the viewer observes authentic gambling, often in a highly stimulating context (e.g. high stakes bets). Streaming content is often broadcast as highlight ‘clips’: short, edited videos that can be viewed on the channel homepage and also shared across social media platforms. For gambling streams, these clips often display the outcomes of single bets showing large 'jackpot' wins, accompanied by the streamer’s intense emotional reaction to winning. It is well recognized that experiencing early big wins in the context of (firsthand) real-money gambling is associated with future gambling problems (Turner et al., 2006), and we propose that the ‘vicarious’ observation of winning may also shift gambling attitudes and intentions. The present study is an online experimental design that will present pre-selected gambling stream clips to participants assigned to two conditions. The experimental group will view a sequence of clips featuring gambling jackpot wins. The control group will view clips with realistic gambling outcomes, i.e. mostly small losses. We will develop these stimuli from a combination of authentic clips and edited Kick footage from longer streams, both as publicly accessible content. The primary dependent variables are (1) attitudes towards gambling, (2) intention to gamble on slot machines, (3) winning probability judgement. We will also measure participants’ affect ratings of the clips as a manipulation check. Trait-level scores on the Gambling-Related Cognitions Scale (GRCS) will be recorded as a possible moderator.
There is ample evidence of the influence of both self-reference and the emotional content of words in language processing and memory. This study examines the conjoint influence of both factors in a variant of the affective HisMine-Paradigm. Participants were presented with pairs of words, that comprised emotional (positive and negative) or neutral words, preceded either by the first-person possessive pronoun "my" (self-reference) or by the definite article "the" (no-reference). Emotional words were divided into emotion-label words (e.g., happiness) and emotion-laden words (e.g., party). Participants were asked to perform an affective evaluation task (i.e., to decide if the word pair conveyed a positive, negative or neutral meaning), followed by a valence rating task (i.e., to rate the word pair in terms of their valence) and an unexpected free recall task. The results for positive words, but not negative words, showed that self-reference facilitated the affective evaluation task and led to more extreme valence ratings. These modulatory effects were observed in emotion-laden words, but not in emotion-label words. These findings support a self-positivity bias, and the literature about the modulation of emotional word processing by self-reference, yet point out the relevance of the distinction between emotion-label words and emotion-laden words.
As part of the reintegration of the traditional and computational lexical research and development activities at the University of Gothenburg, the Swedish Academy's lexical databases are being edited for greater consistency and included in the computational lexical infrastructure of Sprkbanken Text, which in turn is undergoing considerable development in order to meet the requirements of tradi tional lexicography.One aim of this work is to formally interlink these databases with Sprkbanken's Lexical Research Infrastructure.In this chapter we focus on the opportunities for diachronic lexical research offered by the inclusion of one such dataset in this infrastructure.SAOLhist Plus brings together digitized versions of successive editions of the SAOL dictionary, 10 editions covering a timespan of almost a century and a half.Together with some other historical and modern dictionaries and combined with large corpus-extracted vocabularies from the same time interval, we can make wide-ranging and detailed investigations of lexical change in relation to the history of lexicography in Late Modern and Contem porary Swedish.
This randomized controlled study at University of Graz examines the impact of regular practice of an individual self-regulation training on psychophysiological well-being. Participants are randomly assigned to either intervention or control group. Individual self-regulation training is based on a self-regulation method used in NeuroDeescalation®. It combines elements of body movement or touch, breathing and self- encouragement. Participants in the intervention group get videos which support the acquisition of the individual self-regulation training, which should be practiced three times a day over a period of two weeks. In both groups HRV independent of metabolic demands (lmdHRV) is assessed the successive three days before and after intervention period. Furthermore, psychological variables are measured using items of the Positive and Negative Affect Schedule (PANAS), and the Mindful Attention Awareness Scale – State (MAAS – State). We expect that regular practice of an individual self-regulation training leads to higher increases in HRV independent of metabolic demands (lmdHRV), as well as higher increases in positive affect ratings, lower increases in negative affect ratings, and higher increases in state mindfulness from pre- to post- intervention compared to the control group. Statistical analyses will be conducted using mixed Analysis of Variance (ANOVA) to account for between-subjects factor (group) and within-subjects factor (measurement period).
The present dissertation examines the role of context-specific simulations in influencing the complexity of affective experiences, drawing on a constructivist approach to emotion. To link literatures on mental simulation and emotion, in Chapter 1 a connection is made through the grounded theories of cognition. Chapter 2 describes the development of a novel dataset consisting of context-dependent stimuli (i.e., 1,381 picture-word cues derived from 320 pictures-only stimuli) validated through online experiments (NExp1= 1,934; NExp2 = 403). Hence, an investigation of how contextual information influences the affective experience is illustrated, revealing that context more often enhances affective complexity by widening, rather than narrowing, the variation in the between-subject valence ratings. Chapter 3 employs a set of stimuli selected from Chapter 2 in a lab-based experiment in which participants (N = 30) rated affect intensity, and reported which emotions and bodily sensations experienced in response to generating both mental images and verbal thoughts. Mental imagery was found to enhance emotion complexity as reflected in the richness of the reports provided, with affect intensity and autobiographical recall accounting for the effect. Finally, in Chapter 4 the influence of mental imagery on emotion complexity will be studied across the imagery spectrum. To this end, in an online experiment participants (N = 72) completed measures of imagery vividness, alexithymia and gave written reports on how they feel when experiencing emotions at varying levels of valence and arousal, to obtain indexes on the complexity of emotion conceptualization. In line with the predominant literature, the more vivid the visual mental imagery of participants, the less alexithymia was reported, i.e., the less impaired is the process of emotion conceptualization. As highlighted in the final chapter (Chapter 5), overall the present dissertation contributes to deepening the study of the relationship between mental imagery and emotion. Assuming variation as inherent to emotion, consistently through different experimental designs, methods, languages and indexes, it is shown how context-specific simulations enrich the emotional sphere, by enhancing the complexity of affective experiences.
Correction: Task-based explanation for genre effects: Evidence from a dependency treebank
This paper presents a new version of the Spoken Slovenian Treebank (SST), a balanced and representative collection of transcribed spontaneous speech with manually annotated lemmas, part-of-speech tags, morphological features, and syntactic dependencies, recently expanded with over 3,000 newly annotated utterances. After a brief overview of the data sampling, anno-tation, and consolidation processes—presented in detail in previous work—we evaluate the significance of this new language resource for both linguistic research and natural language pro-cessing by first highlighting its distinctive lexical and morphosyntactic features in comparison to writing, and then assessing their impact on the performance of tools for automatic grammatical annotation. Finally, we reflect on the methodological insights gained during treebank creation, discuss the potential of SST for advancing spoken language research, and argue for the necessity of such resources in supporting linguistic diversity in language technology.
Identifying novel neuromodulatory targets for deep brain stimulation (DBS) in psychiatric disorders is an urgent clinical need. Equally critical is the discovery of simple oscillatory biomarkers that bridge behaviour and clinical symptoms, enabling personalized treatment strategies. The bed nucleus of the stria terminalis (BNST), a pivotal output structure of the amygdala, is a potential candidate for DBS due to its key role in regulating fear, emotional valence, and prosocial behaviour. However, owing to the small size, its neural dynamics and functional contributions are poorly understood, precluding behavioural-clinical relevance. In a cross-sectional design, we acquired BNST neural recordings from 23 patients with depression undergoing DBS during two tasks: pain perception with painful/non-painful scenarios and an affect task with emotionally valenced images. We first localized the electrode contacts in the BNST and using their neural recordings for further analysis. We subjected the preprocessed data to time frequency decompositions to find condition differences. The significant clusters were then used to link to the behavioural ratings and clinical symptom severity. Furthermore, cross-frequency interactions were also undertaken. Pain perception elicited late theta and alpha activity (∼1s), with theta activity linked to subjective pain ratings and alpha correlating with anxiety/depression scores and anxiety symptoms post-DBS. Negative imagery induced early theta (∼250 ms), resembling previously reported amygdalar responses, and which link to valence ratings, depression and anxiety symptom severity. These results reveal distinct BNST dynamics in depression: early theta for rapid threat processing and late theta/alpha for complex socio-cognitive responses. Task-dependent theta and alpha activity linked behavioural profiles and symptom severity, highlighting BNST's role in behaviourally and clinically relevant oscillatory patterns, contributing novel insights for advancing precision neuromodulation strategies.
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.
<div> We address the challenge of syntactic parsing for Urdu, a morphologically rich language, and present state-of-the-art results for both constituency and dependency parsing. This paper offers four major contributions: 1) the conversion of the CLE-UTB phrase structure treebank into a dependency treebank by developing language-specific head-word and phrase-to-dependency label mapping rules; 2) a novel sequence labeling scheme that transforms the parsing task into a unified representation; 3) the training of contextualized word representations on a large 220 million tokens Urdu corpus collected from the web; and 4) development of parsing framework using two learning paradigms, single-task and multi-task learning. Several post-processing rules are applied to improve the quality of the automatically converted dependency structure treebank. The proposed sequence labeling scheme enables the use of a shared architecture that learns the syntactic structures from both grammatical structures simultaneously and hence improves generalization. Experiments show that the multi-task learning setup significantly enhances parsing performance, achieving an F1 score of 91.39 for constituency parsing (an improvement of 3.29 points) and a labeled attachment score of 85.69 for dependency parsing (an improvement of 1.49 points). These results demonstrate that learning cross-task representations provides measurable benefits and advances the state of syntactic parsing for Urdu. </div>
The article examines the queer annotated translation of the novel 39 rue de Berne (2013), written by Swiss Cameroonian author Max Lobe, aiming to spark discussions about the translation choices employed.The proposed translation is initially motivated by the representation of dissident sexuality in the work, bringing it closer to Brazilian LGBTQIA+ adult readers, as well as by adopting a questioning stance toward social and linguistic norms, a characteristic of queer.Drawing on passages from the central chapters of the novel, where issues of gender and sexuality are most evident, the research is imbued by theoretical contributions that outline translation strategies to Orlando
Purpose: This study examined the effects of reduced bandwidth and auditory-visual congruence on emotional responses to nonspeech auditory-only and auditory-visual stimuli. Auditory-visual stimuli were picture/sound pairs that were congruent or incongruent in terms of valence (e.g., pleasant picture/unpleasant sound or vice versa). Method: Twenty adults with normal hearing rated the valence (pleasant to unpleasant) and arousal (exciting to calming) of nonspeech auditory-only and auditory-visual stimuli. Auditory stimuli were presented broadband (~125–8000 Hz) or bandpass filtered (800–2000 Hz). Auditory-visual stimuli were created by combining auditory stimuli with a picture of congruent or incongruent valence. Results: Bandpass filtering of auditory-only stimuli reduced the range of valence responses (less pleasant and less unpleasant). With congruent auditory-visual stimuli, bandpass filtering did not affect valence ratings. Incongruent audiovisual stimuli were rated as less pleasant than were congruent, pleasant, auditory-visual stimuli. Arousal ratings were lower with bandpass filtering but were not affected by congruency. Conclusions: Congruent auditory-visual stimuli resulted in more extreme ratings of valence than did auditory-only stimuli. Incongruent auditory-visual stimuli were generally rated as more unpleasant than pleasant, auditory-only stimuli. Consistent with previous studies of low- and high-pass filtering, bandpass filtering (800–2000 Hz) of auditory-only stimuli resulted in more neutral responses, suggesting that frequencies below 800 Hz and above 2000 Hz are important for ratings of valence. Inconsistent with previous low- and high-pass filtering work, bandpass filtering did not affect ratings of congruent auditory-visual stimuli, suggesting a different set of frequencies are important for ratings of valence when visual cues are also available. Supplemental Material: https://doi.org/10.23641/asha.29971387
Background/Objectives: Obesity and insulin resistance (IR) increase the risk of mood disorders, which often manifest during young adulthood. However, neuroelectrophysiological investigations of whether adiposity and IR modify electrocortical activity and emotional processing outcomes remain underexplored, particularly in young adults. Therefore, this study used electroencephalography (EEG) to investigate whether obesity and/or IR moderate the relationships between brain potentials and affective processing in younger adults. Methods: Thirty younger adults completed a passive picture-viewing task utilizing the International Affective Picture System while real-time electroencephalography was simultaneously recorded. Two event-related potentials—early posterior negativity (EPN) and late positive potential (LPP)—were quantified. Affective processing parameters included 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. Results: In the Negative−Neutral condition, lean and insulin-sensitive participants gave less negative valence ratings to unpleasant versus neutral images when late-window LPP amplitudes were larger, whereas this relationship was reversed in participants with obesity and absent in those with IR. Contrariwise, neither obesity nor IR moderated LPP responses to affective processing parameters in the Positive−Neutral or Negative−Positive valence conditions. Additionally, obesity and IR did not moderate the links between EPN responses and affective processing parameters in any of the valence conditions. Conclusions: Lean, insulin-sensitive young adults showed attenuated affective processing of unpleasant stimuli through stronger neural responses, whereas neural responses to pleasant stimuli did not vary across levels of body fat or IR. These preliminary findings suggest that both obesity and IR increase the vulnerability to mood disorders in young adulthood.
Based on the English-Chinese Parallel Corpus of Children’s Literature and the Corpus of Chinese Children’s Literature, this study investigates the feature of normalization in the Chinese translation of English children’s literature. Normalization refers to the adaptation of foreign features in the source text to comply with the cultural and linguistic norms of the target culture. The study analyzes both macro and micro levels of language features in translated children’s literature, comparing them with original Chinese and English texts. The findings reveal a clear trend towards normalization, evidenced by shorter sentences, increased repetition of high-frequency words, a lower frequency of hapax legomena, and a higher textual readability in translated Chinese versions. Furthermore, linguistic structures such as reduplication, modal particles, “把” (BA), and “得” (DE) constructions are found to occur at rates comparable to or significantly higher than those in the original Chinese corpus. This paper argues that normalization is a creative outcome, molded by translators aligning with reader expectations, conscientiously considering the psychological characteristics of child readers, and adapting to social, cultural, and market influences. The study contributes to understanding linguistic features of translated children’s literature, sheds light on translation universals, and underscores the dynamic interplay between normalization and translator creativity.
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
Abstract Memory for emotional information is greater than for non-emotional information and is enhanced by sleep-related consolidation. Previous studies have focused on emotional arousal and valence of established stimuli, but what is the effect of sleep on newly acquired emotional information? Figurative expressions, which are pervasive in everyday communication, are often rated as higher in emotionality than their literal counterparts, but the effect of emotionality on the learning of metaphors, and the effect of sleep on newly acquired emotionally negative, positive and neutral language, is as yet poorly understood. In this study, participants were asked to memorise conventional (e.g. ‘ sunny disposition’ ) and novel (e.g. ‘ cloudy disposition’ ) metaphorical word pairs varying in valence, accompanied by their definitions. After a 12-hour period of sleep or wake, participants were tested on their recognition of word pairs and recall of definitions. We found higher arousal ratings were related to increased recognition and recall performance. Furthermore, sleep increased the accurate recognition of all word pairs compared to wake but also reduced the valence of word pairs. The results indicate better memory for newly acquired emotional stimuli, a benefit of sleep for memory, but also a reduction in emotional arousal as a consequence of sleep consolidation.
Contextual processing enables the brain to integrate environmental cues for adaptive emotional perception. It is crucial to understand how this ability operates in dynamic environments of short video viewing and how the brain supports it. In this study, we utilized behavioral and neuroimaging experiments to examine contextual processing during short video viewing. Compared with single-face clips, face-context-face sequences elicited coherent emotional perceptions of neutral faces from emotional contexts. A distributed brain network was involved in the top-down modulation of contextual processing. Temporoparietal junction (TPJ) and precuneus showed sustained engagement during context integration. Activity in TPJ and insula was associated with valence and arousal ratings, respectively. Under negative contexts, global functional segregation facilitated contextual processing, and weaker TPJ-insula connectivity corresponded to stronger contextual effects. This study advances the understanding of contextual processing in the digital media age and may inform future investigations into neural correlates of contextual processing dysfunction in psychiatric conditions.
This paper presents an experiment comparing six models to identify state-of-the-art models for Ancient Greek: a morphosyntactic parser and a lemmatizer that are capable of annotating in accordance with the Ancient Greek Dependency Treebank annotation scheme.A normalized version of the major collections of annotated texts was used to (i) train the baseline model Dithrax with randomly initialized character embeddings and (ii) fine-tune Trankit and four recent models pretrained on Ancient Greek texts, namely GreBERTa and PhilBERTa for morphosyntactic annotation and GreTA and PhilTa for lemmatization.A Bayesian analysis shows that Dithrax and Trankit are practically equivalent in morphological annotation, while syntax is best annotated by Trankit and lemmata by GreTa.The results of the experiment suggest that token embeddings are not sufficient to achieve high UAS and LAS scores unless they are coupled with a modeling strategy specifically designed to capture syntactic relationships.The dataset and best-performing models are made available online for reuse.
Emotion polyregulation involves employing multiple strategies to manage stress, with effectiveness depending on their alignment with personal and situational contexts. The ideal sequence of strategies to reduce negative affect remains unclear. This study aimed to compare sequences of attention deployment and cognitive reappraisal tactics (i.e., reinterpretation and psychological distancing), while also examining contextual factors like image intensity. Seventy participants (n = 66, Age = 22.04 ± 5.8; 19% Male; 48% White) completed a negative image rating task across four blocks of 24 trials: look neutral, look negative, and regulate negative. In regulate trials, participants switched regulation strategies at 5 s and rating their negative affect at 5 and 10 s. Blocks varied by cue sequence: reengage (attention deployment first) or unburden (cognitive reappraisal tactic first). In a linear mixed model, the unburden condition led to lower negative affect ratings compared to the reengage condition t(1157) = -5.12, p <.001, and showed a unique, significant decrease in negative affect from cue 1 to cue 2, t(1157) = 6.05, p <.001, indicating a synergistic effect. While cognitive reappraisal tactics did not benefit from the reengage condition, it remained an effective means of reducing negative affect in either sequence position. High-intensity images predicted higher negative affect ratings overall (p <.001), and the synergistic effects were heightened during high-intensity images. This study highlights the potential of sequential emotion regulation strategies—particularly using attention deployment as relief after cognitive reappraisal—to improve emotional outcomes, with promising implications for clinical therapy.