Syntactic Structure Research Articles

Translating the Public Sphere: Analyzing Linguistic and Cultural Dimensions in Publicistic Texts

This study explores the challenges and strategies involved in translating publicistic texts, which are characterized by their rich use of figurative language, complex syntactic structures, and culturally specific references. Publicistic texts play a critical role in shaping public discourse by conveying ideological and social narratives; however, their translation requires more than a literal rendering. Drawing on theories of figurative language (Glucksberg & McGlone, 2001) and intercultural communication (Iriye, 1979; Kulikova et al., 2017), the research examines how translators navigate linguistic complexities—such as idiomatic expressions and non-standard syntactic forms—while also adapting culturally embedded elements for target audiences. Employing a qualitative methodology that integrates comparative discourse and content analyses of selected texts and their translations, the study identifies common translation strategies, including domestication and the use of explanatory notes, as well as the inherent tensions between fidelity to the source and cultural adaptation. The findings underscore the translator’s role as an active mediator who shapes the final text, influencing its ideological and cultural impact. This research contributes to translation studies by offering insights into the effective handling of linguistic and cultural nuances in the public sphere, with implications for both academic practice and professional training.

Lexical semantics trumps syntax during noun composition in predication and modification contexts: insights from the N400 and alpha and beta band synchronisation

ABSTRACT Compositionality is the thesis that the meanings of complex expressions are derived from the meanings of their constituent parts and syntactic structure. We used a new experimental paradigm to study how syntactic mode of composition (predication vs modification) and lexical semantic properties of the expressions combined (intersective vs subsective vs privative adjectives vs verbs) affect electroencephalographic (EEG) signals. We compared nouns in sentences composing either with a verb (predication) or an adjective (modification) to conditions in which the same noun and adjective, or verb, were separated by a syntactic boundary, preventing composition locally. Event-related potentials (ERPs) and alpha-beta power were modulated primarily by the lexical semantic properties of the words combined, not by the syntactic mode of composition. Our findings raise questions about the neurobiological import of linguistic theories that distinguish cases of composition according to syntactic variables, while abstracting away from the specific semantic contributions of the words involved.

From speech signal to syntactic structure: A computational implementation

This paper presents a new computational implementation bridging several modules of grammar from phonetics to phonology to syntax. The system takes as input a speech signal annotated with syllables, interprets the phonetic data in phonological/prosodic terms, matches the data against a lexicon and makes the results available to a linguistically deep computational grammar. The system is showcased by means of syntactically ambiguous structures in German which can be disambiguated based on prosodic constituency information. A system evaluation with the German data showed good results for this new combination of automatic speech signal analysis and computational grammars, which takes a significant step towards a linguistically fine-grained computational analysis and hence towards real automatic speech understanding.

Konstruksi Realitas Arogansi Patwal di Platform Digital: Analisis Framing Pemberitaan Kasus Patwal RI 36 di Media Online

This study aims to analyze the construction of the reality of the arrogance of RI 36 Patwal officers on digital platforms through a framing analysis approach. Using a descriptive qualitative method, this research examines how social media and online reporting shape public perceptions of the incident. The data collected were narratives, news articles, posts, and comments on social media related to the patwal arrogance incident. The analysis was conducted using the agih method to examine framing elements, such as syntactic structure, vocabulary, and rhetoric in the text that lead to the formation of public opinion. The results showed that the framing formed by social media and online news was more dominant towards a negative perception of Patwal officers, highlighting arrogant actions as a symbol of abuse of power. Despite clarification efforts from related parties, the public opinion formed through the initial framing remains difficult to change. This research reveals how framing on digital platforms has a major influence in shaping social reality and perceptions of the actions of state apparatus.

Syntactic Structural Development in Chinese deaf Children Aged 4-7 Years with Cochlear Implants.

Using the syntactic priming paradigm, this study investigated abstract syntactic knowledge of Chinese transitive structures (i.e., subject-verb-object [SVO], BA, and BEI) in deaf children with cochlear implants (CIs). Specifically, we focused on the differences in the development of various syntactic structures (within CI children and compared with their typically hearing children) and the possible individual differences during this process. Results showed that both CI and hearing children exhibited structural priming for all syntactic structures (i.e., SVO, SbaOV structure [agent-patient ordering], and ObeiSV structure [patient-agent ordering]) after comprehending and repeating the prime sentence regardless of verb repetition. However, verb repetition induced an intense abstract priming effect in CI children but not hearing children, with the lexical boost effect more significant for SVO and BA structures. In addition, CI children's working memory capability modulated the production of the BA structure but not SVO and BEI structures.

EmoAtlas: An emotional network analyzer of texts that merges psychological lexicons, artificial intelligence, and network science.

We introduce EmoAtlas, a computational library/framework extracting emotions and syntactic/semantic word associations from texts. EmoAtlas combines interpretable artificial intelligence (AI) for syntactic parsing in 18 languages and psychologically validated lexicons for detecting the eight emotions in Plutchik's theory. We show that EmoAtlas can match or surpass transformer-based natural language processing techniques, BERT or large language models like ChatGPT 3.5 or LLaMAntino, in detecting emotions from Italian and English online posts and news articles (e.g., achieving 85.6 accuracy in detecting anger in posts vs the 68.8 value of ChatGPT and 89.9% value for BERT). EmoAtlas presents important advantages in terms of speed and absence of fine-tuning, e.g., it runs 12x faster than BERT on the same data. Testing EmoAtlas' and easily trainable transformers' relevance in a psychometric task like reproducing human creativity ratings for 1071 short texts, we find that EmoAtlas and BERT obtain equivalent predictive power (fourfold cross-validation, , ). Combining BERT's semantic features with EmoAtlas' emotional/syntactic networks of words gets substantially better at estimating creativity rates of stories ( , ). This indicates an interplay between the creativity of narratives and their semantic, emotional, and syntactic structure. Via interpretable emotional profiles and syntactic networks, EmoAtlas can also quantify how emotions are channeled through specific words in texts, e.g., how did customers frame their ideas and emotions towards "beds" in hotel reviews? We release EmoAtlas as a standalone "text as data" computational tool and discuss its impact in extracting interpretable and reproducible insights from texts.

Aspect category sentiment analysis based on pre-trained BiLSTM and syntax-aware graph attention network

Aspect Category Sentiment Analysis (ACSA) is a fine-grained sentiment analysis task aimed at predicting the sentiment polarity associated with aspect categories within a sentence.Most existing ACSA methods are based on a given aspect category to locate sentiment words related to it. When irrelevant sentiment words have semantic meaning for the given aspect category, it may cause the problem that sentiment words cannot be matched with aspect categories. To address the aforementioned issue, this paper proposes a novel approach for ACSA utilizing pre-trained Bidirectional Long Short-Term Memory (BiLSTM) and syntax-aware graph attention network. To address the issue of insufficient existing annotated datasets, a method of using transfer learning is proposed. Firstly, the BiLSTM model is used to pre-train on the document-level sentiment analysis dataset, and the obtained pre-training parameters are transferred to the aspect-level task model. Then, a syntax-aware graph attention network model is proposed to make full use of the syntactic structure and semantic information in the text, and combine the knowledge learned in pre-training to achieve the ACSA task. The performance evaluation of this method is carried out on five user comment text datasets, and the comprehensive ablation experiments prove that this method performs best compared with baseline models.

Flowing With the Syntax: The Influence of Taoism on Syntactic Priming Effects

Syntactic priming is a linguistic phenomenon where the exposure to a specific grammatical structure increases the likelihood that the same structure will be used in subsequent language production. Previous research has shown that these syntactic processes are influenced by a broad range of linguistic, cognitive, and social factors. In the present research, we focused on the role of religious systems in shaping syntactic priming in dialog. Based on the observation that the Taoist concept of “moving with flow” encourages individuals to adapt to the natural flow of life and circumstances, we hypothesized that Taoists might modify their syntactic choices to foster better connections with their interlocutors. We conducted two studies to test our theoretical perspective. As predicted, Study 1 found that Taoists were more likely to mirror the syntax used by their interlocutors in dialog than their atheist counterparts. In Study 2, we compared the magnitude of syntactic priming effects between Taoists and Buddhists. The results showed that Taoists demonstrated a stronger preference for using the same syntactic structure as their conversational partners than Buddhists. In sum, our findings provide the first empirical evidence that beliefs and values associated with religious systems exert a significant influence on syntactic priming effects.

Decoding words during sentence production: Syntactic role encoding and structure-dependent dynamics revealed by ECoG.

Sentence production is the uniquely human ability to transform complex thoughts into strings of words. Despite the importance of this process, language production research has primarily focused on single words. However, it remains a largely untested assumption that the principles of word production generalize to more naturalistic utterances like sentences. Here, we investigate this using high-resolution neurosurgical recordings (ECoG) and an overt production experiment where patients produced six words in isolation (picture naming) and in sentences (scene description). We trained machine learning classifiers to identify the unique brain activity patterns for each word during picture naming, and used these patterns to decode which words patients were processing while they produced sentences. Our findings confirm that words share cortical representations across tasks, but reveal a division of labor within the language network. In sensorimotor cortex, words were consistently activated in the order in which they were said in the sentence. However, in inferior and middle frontal gyri (IFG and MFG), the order in which words were processed depended on the syntactic structure of the sentence. Deeper analysis of this pattern revealed a spatial code for representing a word's position in the sentence, with subjects selectively encoded in IFG and objects in MFG. Finally, we argue that the processes we observe in prefrontal cortex may impose a subtle pressure on language evolution, explaining why nearly all the world's languages position subjects before objects.

A magnitude-independent neural code for linguistic information during sentence production.

Humans are the only species with the ability to convey an unbounded number of novel thoughts by combining words into sentences. This process is guided by complex semantic and abstract syntactic representations. Despite their centrality to human cognition, the neural mechanisms underlying these systems remain obscured by inherent limitations of non-invasive brain measures and a near total focus on comprehension paradigms. Here, we address these limitations with high-resolution neurosurgical recordings (electrocorticography) and a controlled sentence production experiment. We uncover distinct cortical networks encoding word-level, semantic, and syntactic information. These networks are broadly distributed across traditional language areas, but with focal sensitivity to syntactic structure in middle and inferior frontal gyri. In contrast to previous findings from comprehension studies, these networks are largely non-overlapping, each specialized for just one of the three linguistic constructs we investigate. Most strikingly, our data reveal an unexpected property of higher-order linguistic information: it is encoded independent of neural activity levels. We propose that this "magnitude-independent coding" scheme represents a novel mechanism for encoding information, reserved for higher-order cognition more broadly.

A Study on Pivot Sentences Acquisition of International Students based on Natural Language Processing Technologies

In the context of the rapid development of globalized education, the demand for Chinese language learning among international students continues to rise. As a special and complex sentence structure in Chinese, the acquisition of "pivot sentences" is of great importance. Traditional acquisition research methods often rely on manual annotation and empirical analysis, which are difficult to handle large-scale data and are subject to a high degree of subjectivity. With the rapid advancement of natural language processing (NLP) technologies, new opportunities have emerged for research in this field. This paper utilizes various techniques from NLP, such as pre-trained language models (e.g., BERT, GPT) and grammar error detection methods based on Bayesian classification algorithms, to automatically analyze the production of pivot sentences by international students. These technologies enable precise identification of grammatical errors, syntactic structure anomalies, and inappropriate word usage in serial verb constructions. By deeply exploring the underlying causes of error patterns, this research provides a comprehensive and systematic understanding of the acquisition process of pivot sentences by international students, offering strong support for targeted teaching and promoting the advancement of Chinese as a second language education to a new level.

The Child’s Language System during the Vocabulary Explosion: Individual and Common Trends

A longitudinal diary study on the formation of two young girls’ individual language systems was carried out. In both cases, the general language ability was tracked by considering its key components, including the phonetic, lexical, morphological, and syntactic ones, as well as imitation skills and early metalinguistic awareness. The relation between these components (autonomy or mutual influence) was examined. The MacArthur–Bates Communicative Development Inventories (CDI) were used as an auxiliary tool. The findings of the two case studies were compared with the published results of a systemic analysis based on the extensive MacArthur–Bates-CDI database on various components of general language ability. The comparisons revealed shared and individual language acquisition patterns in the early stages of speech ontogenesis. The obtained data are consistent with those reported in previous research: in the early stage of language acquisition, the speech of the girls was marked by an interaction between the phonetic (articulation of complex three- or four-syllable words), lexical (vocabulary growth), and morphological (learning grammatical categories) components, while the syntactic component progressed relatively autonomously; and then, during the later stage, morphological skills served more as a supportive mechanism that facilitated the construction of grammatically accurate syntactic structures.

Framing Pemberitaan Atlet Voli Megawati Hangestri di Liga Voli Korea pada Media bola.com dan okezone.com

Sports news today is increasingly being looked at by the public, unfortunately the presentation of news is not entirely paying attention to the objective and value aspects of the news, especially the view of the value of women in the news about female athletes who are often considered less proportional and cause other views that are not true. Using the constructivism paradigm to find out how athlete Megawati Hangestri was framed through the online media Bola.com and Okezone.com during her match in the 2024 Korean Volleyball League with 8-9 news stories each to study, using the framing analysis developed by Zhongdang Pan and Gerald M. Kosicki classifying framing devices into four main elements, namely syntactic structure, script structure, thematic structure, and rhetorical structure. The results found that Bola.com online media framed Megawati Hangestri as a professional athlete and hero in the eyes of the Indonesian people. Meanwhile, Okezone.com framed Megawati Hangestri as an inspirational influencer. Both produce positive narratives by accentuating Megawati Hangestri's achievements so as to form a positive image and be able to change public perceptions.

Understanding Syntactic Deviations of Sentence Derivation in Student English: A Study within the Minimalist Program

This study explores the syntactic deviations in written English by freshmen EFL students at Saudi universities focusing on their implications for understanding syntactic competence. The research investigates 105 students' compositions to pinpoint the most frequent and notable syntactic errors, employing the Minimalist Program (MP) by Noam Chomsky. The objective is to root these deviations within a solid theoretical background, thereby scientifically elucidating their causes and enhancing strategies for explaining syntax using the latest Chomskyan MP approach. The findings reveal that the most common syntactic deviations include verb complement errors (22.43%), tense and agreement discrepancies, (21.14%) and omissions of critical syntactic elements like prepositions (9.28%) and determiners (3.42%). These errors are systematically categorized and analyzed using MP mechanisms, which facilitates a deeper understanding of the theoretical bases upon which syntactic structures are formed and analyzed. This methodological approach helps in understanding the origins of observed errors, providing a well-grounded justification for deeming certain expressions incorrect in daily language practices. Ultimately, this analysis not only illuminates the common challenges faced by these learners but also suggests more effective teaching strategies. By leveraging a profound and clear understanding of MP, the study provides insights into the practical and deep reasons behind linguistic errors, enhancing both theoretical knowledge and instructional practices in the field of EFL.

Hybrid Compound Formation in Classical Papiamentu

Since its genesis, Papiamentu has been influenced by several lexifiers. This study examines etymological patterns of hybrid formation in Classical Papiamentu (CP), mainly focusing on Iberian and Dutch contributions. Studying morphosyntactic functions in hybrid words can reveal typological relations between Creole languages. Thus, this study aims to expand linguistic knowledge about CP and Creole languages in general. The corpus contains sixty-one hybrid compound words from CP, mostly compound nouns and compound verbs, compiled from the Woordenlijst, the first Papiamentu vocabulary, printed in 1859. The process of classifying hybrid words is described, and examples are provided. Hybrid etymological patterns are quantified in both anterior and posterior positions. The frequency of etymological patterns is displayed in separate tables for nouns and verbs. The data analysis focuses on morphosyntactic relations between internal components based on etymological occurrences. The compounding syntax of CP is the basis for arguing in favor of a more significant Iberian influence over word formation in CP. Data analysis reveals that Iberian syntactic structures are replicated in hybrid formations even when both components are Dutch loans. The overall prevalence of Iberian lexicon occupying the head position in both compound nouns and compound verbs supports this argument. The results also show a preference for syntactic phrases to link components within a compound.

Neural correlates of auditory comprehension and integration of sanskrit verse: a functional MRI study.

In this investigation, we delve into the neural underpinnings of auditory processing of Sanskrit verse comprehension, an area not previously explored by neuroscientific research. Our study examines a diverse group of 44 bilingual individuals, including both proficient and non-proficient Sanskrit speakers, to uncover the intricate neural patterns involved in processing verses of this ancient language. Employing an integrated neuroimaging approach that combines functional connectivity-multivariate pattern analysis (fc-MVPA), voxel-based univariate analysis, seed-based connectivity analysis, and the use of sparse fMRI techniques to minimize the interference of scanner noise, we highlight the brain's adaptability and ability to integrate multiple types of information. Our findings from fc-MVPA reveal distinct connectivity patterns in proficient Sanskrit speakers, particularly involving the bilateral inferior temporal, left middle temporal, bilateral orbitofrontal, and bilateral occipital pole. Voxel-based univariate analysis showed significant activation in the right middle frontal gyrus, bilateral caudate nuclei, bilateral middle occipital gyri, left lingual gyrus, bilateral inferior parietal lobules, and bilateral inferior frontal gyri. Seed-based connectivity analysis further emphasizes the interconnected nature of the neural networks involved in language processing, demonstrating how these regions collaborate to support complex linguistic tasks. This research reveals how the brain processes the complex syntactic and semantic elements of Sanskrit verse. Findings indicate that proficient speakers effectively navigate intricate syntactic structures and semantic associations, engaging multiple brain regions in coordination. By examining the cognitive mechanisms underlying Sanskrit verse comprehension, which shares rhythmic and structural features with music and poetry, this study highlights the neural connections between language, culture, and cognition.

Czy we współczesnej białoruszczyźnie istnieją dwie normy językowe?

The article answers the question whether there are two separate linguistic norms in the modern Belarusian language. On the basis of grammars, dictionaries, textbooks, educational programs and scientific articles, the author highlights the differences between the two sets of spelling rules operating in contemporary Belarusian, discusses opposing tendencies in the method of assimilation of loanwords, presents variants of grammatical endings, describes separate word-formation models and highlights the differences in lexis and syntactic structures. In this way, he proves the presence of two separate linguistic norms in the modern Belarusian language. The first: official – in accordance with the so-called narkamauka, i.e. the rules presented in current textbooks on spelling and grammar of the Belarusian language, which draws many lexical, word-formation and syntactic patterns from the Russian language, and the second norm: purist - based on the so-called tarashkievica, i.e. spelling rules introduced by Bronisław Taraszkiewicz in a textbook published in 1918 in Vilnius. At the end of the article, the author shares with the reader her own reflections on the possibility of unifying the Belarusian norms in the future.

Pantograph: A Fluid and Typed Structure Editor

Structure editors operate directly on a program’s syntactic tree structure. At first glance, this allows for the exciting possibility that such an editor could enforce correctness properties: programs could be well-formed and sometimes even well-typed by construction. Unfortunately, traditional approaches to structure editing that attempt to rigidly enforce these properties face a seemingly fundamental problem, known in the literature as viscosity . Making changes to existing programs often requires temporarily breaking program structure—but disallowing such changes makes it difficult to edit programs! In this paper, we present a scheme for structure editing which always maintains a valid program structure without sacrificing the fluidity necessary to freely edit programs. Two key pieces help solve this puzzle: first, we develop a novel generalization of selection for tree-based structures that properly generalizes text-based selection and editing, allowing users to freely rearrange pieces of code by cutting and pasting one-hole contexts; second, we type these one-hole contexts with a category of type diffs and explore the metatheory of the system that arises for maintaining well-typedness systematically. We implement our approach as an editor called Pantograph , and we conduct a study in which we successfully taught students to program with Pantograph and compare their performance against a traditional text editor.

Expression of patient and caregiver uncertainty in view of decision-making in online health communities.

On the backdrop of the current debate on shared-decision making in healthcare, we are interested in understanding how uncertainty is managed when patients and/or their caregivers resort to online health communities (OHCs) for advice regarding decisions on aspects of the disease they are not fully sure of. More specifically, we present initial results concerning the expression of uncertainty in OHCs regarding decisions that have to be made about a specific illness. Our goal is to observe how patients and/or their caregivers express uncertainty regarding information they received from specialists. This can help us understand how non-experts try to cope with information they do not fully understand. Based on a collection of interactional data taken from two Italian OHCs, our analysis focuses on the sequences in which someone asks for advice on a certain line of action and obtains an answer. We follow a mainly qualitative approach, which includes case-based qualitative analyses. More specifically, we observe uses and functions of some lexical items (evidentemente (lit., evidently), teoricamente (lit., theoretically)) and syntactic structures (specifically clauses containing the verb dire (to say)) that convey a sense of uncertainty in relation to information provided by others. Our results show different types of uncertainty, providing insights into the effort non-experts make in dealing with expert knowledge and unclear situations determined by the illness and its management. Our results can be used to improve healthcare professionals' training regarding their role as mediators between specialized and everyday knowledge.

Language-specific neural dynamics extend syntax into the time domain.

Studies of perception have long shown that the brain adds information to its sensory analysis of the physical environment. A touchstone example for humans is language use: to comprehend a physical signal like speech, the brain must add linguistic knowledge, including syntax. Yet, syntactic rules and representations are widely assumed to be atemporal (i.e., abstract and not bound by time), so they must be translated into time-varying signals for speech comprehension and production. Here, we test 3 different models of the temporal spell-out of syntactic structure against brain activity of people listening to Dutch stories: an integratory bottom-up parser, a predictive top-down parser, and a mildly predictive left-corner parser. These models build exactly the same structure but differ in when syntactic information is added by the brain-this difference is captured in the (temporal distribution of the) complexity metric "incremental node count." Using temporal response function models with both acoustic and information-theoretic control predictors, node counts were regressed against source-reconstructed delta-band activity acquired with magnetoencephalography. Neural dynamics in left frontal and temporal regions most strongly reflect node counts derived by the top-down method, which postulates syntax early in time, suggesting that predictive structure building is an important component of Dutch sentence comprehension. The absence of strong effects of the left-corner model further suggests that its mildly predictive strategy does not represent Dutch language comprehension well, in contrast to what has been found for English. Understanding when the brain projects its knowledge of syntax onto speech, and whether this is done in language-specific ways, will inform and constrain the development of mechanistic models of syntactic structure building in the brain.