Latest Articles

• A Systematic Literature Review on Enhancing Sarcasm Detection in Online Reviews through Emotional Transition Analysis and Contextual Embedding Techniques
  by Stephen Olamilekan Adedigba, Mohamad Hardyman Barawi, Ebuka Ibeke and Norazuna Norahim
  J. CS. 2025, 26(3), 227-269;
  Abstract Analysing online reviews is crucial for understanding user sentiments, yet sarcasm often hinders accurate sentiment evaluation. In this systematic literature review (SLR), we addressed the challenging task of sarcasm detection in online reviews, focusing on two key aspects: emotional transitions wit... [Read more]
  Abstract Analysing online reviews is crucial for understanding user sentiments, yet sarcasm often hinders accurate sentiment evaluation. In this systematic literature review (SLR), we addressed the challenging task of sarcasm detection in online reviews, focusing on two key aspects: emotional transitions within reviews and the capabilities of contextual embedding techniques. Due to the context-sensitive and multifaceted nature of sarcasm, most traditional natural language processing (NLP) systems struggle to detect sentiment accurately. To identify sentiment shifts indicative of sarcasm, this systematic literature review (SLR) examines existing literature on emotion transitions within review texts. This review aims to illuminate the linguistic cues associated with sarcastic sentiment reversals. In order to identify these cues more effectively, we further explore the application of advanced contextual embedding models, such as BERT and ELMo, for their ability to detect and analyse sarcastic expressions. By synthesising these findings, we offer a comprehensive overview of current approaches to sarcasm detection in sentiment analysis. Additionally, this review critically analyses the limitations of existing methods and proposes potential avenues for improvement. We aim to explicate the effectiveness of sarcasm detection in sentiment analysis applications used on social media platforms like X (Twitter), Reddit, Facebook, and WeChat. In brief, this review provides valuable insights into the field of sentiment analysis and emotion detection, paving the way for the development of NLP systems with a refined ability to discern intricate emotional and contextual embedding in online reviews. [Collapse]
  Keywords: sarcasm detection, emotion analysis, contextual embedding, natural language processing, sentiment analysis, BERT, online reviews
• Facial Color and Semantic Priming in the Perception of Emotional Expressions
  by Chungyu Park & Jiyoun Choi
  J. CS. 2025, 26(3), 271-288;
  Abstract Facial expressions are primary cues for emotion perception, yet their interpretation is influenced by contextual factors. Color is one such factor, carrying affective meanings that may affect how emotional expressions are recognized. The present study examined how red and yellow facial colors affect... [Read more]
  Abstract Facial expressions are primary cues for emotion perception, yet their interpretation is influenced by contextual factors. Color is one such factor, carrying affective meanings that may affect how emotional expressions are recognized. The present study examined how red and yellow facial colors affect the recognition of anger and happiness expressions in Korean participants, and whether these effects are modulated by semantic priming. Participants first completed a Stroop task designed either to strengthen color–emotion associations (congruent priming condition) or to present colors in a non-associative manner (incongruent priming condition). They then judged facial expressions overlaid with red or yellow hues. Results showed that red facilitated recognition of angry faces, whereas yellow facilitated recognition of happy faces, with these effects being robust under the semantic priming condition. Reaction time analyses further revealed a facilitative effect of yellow on happy face recognition, while the facilitation of red on anger was less consistent. These findings suggest that color acts not only as a perceptual cue but also as a conceptually grounded signal that interacts with higher-order semantic processes in shaping emotional face perception. [Collapse]
  Keywords: emotion, color, facial expression, semantic priming
• A Corpus-Based Case Study of Human Insight into Concepts and Reality and Its Philosophical Implications: Japanese Jibun ‘Self’ and Shiawase ‘Happiness’
  by Yoko Mizuta
  J. CS. 2025, 26(3), 289-335;
  Abstract This paper aims to explore the dynamic aspect of deepening our understanding of concepts and reality that involves experiences and thought at later stages of our lives along personal and social dimensions. We take a linguistic approach, using corpus data focusing on examples of Japanese hontōno {jib... [Read more]
  Abstract This paper aims to explore the dynamic aspect of deepening our understanding of concepts and reality that involves experiences and thought at later stages of our lives along personal and social dimensions. We take a linguistic approach, using corpus data focusing on examples of Japanese hontōno {jibun/ shiawase} ‘true {self/ happiness}’ and their lexical variants. Insights about the concept and reality of hontōno {jibun/ shiawase} are identified and organized in terms of classification and contrast. Then qualitative and quantitative analyses of the corpus data that are annotated with the identified insights are provided. The analysis demonstrates that the meaning of jibun and shiawase extends beyond lexical and encyclopedic knowledge and reflects the process of seeking and approaching truth with a critical stance toward the world around us (e.g. a common sense of values). Hontōno is fundamentally involved in this process and functions as a contrast marker reflecting human critical thinking. The discussion includes a comparison between the empirical insights about shiawase and Aristotle’s philosophical thought on eudimonia ‘happiness’ as presented in Nicomachean Ethics. The findings suggest that the proposed corpus-based analysis serves as an effective means for obtaining and utilizing empirical data for the exploration of philosophical issues as well as lexical semantics and pragmatics. [Collapse]
  Keywords: concepts and reality, critical thinking, corpus analysis, Japanese data, annotated data, self, happiness, philosophical implications
• Combinatory Logic, Semantics and Cognition
  by Miloud Rouabhi1 & Jean-Pierre Desclés
  J. CS. 2025, 26(2), 111-158;
  Abstract Combinatory Logic (CL) of H. B. Curry is a formalism where any operators can be composed and transformed by abstract operators (called combinators), without using bound variables. The actions of combinators are presented by introduction and elimination rules in the Gentzen’s.natural deduction style.... [Read more]
  Abstract Combinatory Logic (CL) of H. B. Curry is a formalism where any operators can be composed and transformed by abstract operators (called combinators), without using bound variables. The actions of combinators are presented by introduction and elimination rules in the Gentzen’s.natural deduction style. By explicit deductions using combinators, it is shown how linguistic expressions are analyzed and linked to their structured semantic and cognitive representations where different types of cognitive primitives (operators and relators) are composed together. CL is used in the theoretical model of GRACE (GRammar of Applicative, Cognitive and Enunciative operations) to explain how activity of language, expressed by natural languages, works with changes of metalinguistic representations between different levels of processing: from a linguistic level towards a semantic-cognitive interpretation, according to a bottom up processing and from cognitive schemes towards their linguistic expressions, according to a top down processing. Some illustrating examples of changes of representations are given; one example is about a semantic representation of the verbal unit ‘go out of’, other examples are about the semantic representations of aspects and tenses. [Collapse]
  Keywords: Operators vs operands, applicative expressions, combinators, semantic and cognitive representations, predicative schema, cognitive scheme, reduction to a normal form, intermediary metalinguistic representations
• On Anaphoric Bare Nouns in Korean: Their Interaction with the Particle NUN
  by Myung-Kwan Park
  J. CS. 2025, 26(2), 159-187;
  Abstract This paper examines anaphoric bare nouns in Korean, concentrating on their interaction with the topic marker NUN. Unlike in English, Korean bare nouns (without determiners) can function as anaphoric definites by referring back to their antecedents introduced in prior discourse. However, Kim (2023) a... [Read more]
  Abstract This paper examines anaphoric bare nouns in Korean, concentrating on their interaction with the topic marker NUN. Unlike in English, Korean bare nouns (without determiners) can function as anaphoric definites by referring back to their antecedents introduced in prior discourse. However, Kim (2023) and Tomioka (2024) recently note that when marked with NUN or WA, the displaced bare nouns in apparent topic position require a preceding definite demonstrative to serve this function, a pattern observed in both Korean and Japanese. By focusing on Korean cases and comparing them with Chinese counterparts, we argue that the definite demonstrative ku ‘that’ on the displaced NUN-marked bare nouns in apparent topic position is necessary for reasons beyond simply encoding anaphoric definiteness. In a non-contrastive context where only one referent has been introduced in prior discourse, NUN marking on the displaced anaphoric bare noun in apparent topic position in the following sentence results in infelicity, as it inherently induces a contrastive topic reading. However, this effect is neutralized when the noun at hand is preceded by the definite demonstrative. [Collapse]
  Keywords: bare noun, anaphoric definite, NUN marking, topic or contrast, definite demonstrative
• Investigating LLMs’ Processing of Binding Relations in Korean
  by Kangsan Noh, Eunjeong Oh and Sanghoun Song
  J. CS. 2025, 26(2), 189-216;
  Abstract This study examines the linguistic competence of large language models (LLMs) by evaluating their performance on anaphoric binding in Korean, a language that permits both local and long-distance binding. Using 280 test sentences adapted from prior experiments on native speakers’ preferences for loca... [Read more]
  Abstract This study examines the linguistic competence of large language models (LLMs) by evaluating their performance on anaphoric binding in Korean, a language that permits both local and long-distance binding. Using 280 test sentences adapted from prior experiments on native speakers’ preferences for local versus long-distance binding, we tested three Generative Pretrained Transformers—GPT-3.5-turbo, GPT-4, and GPT-4o—on their ability to resolve reflexives and pronouns. Across all models, we observed a strong and consistent preference for long-distance binding, even in contexts where native Korean speakers reliably favor local antecedents. This pattern was especially pronounced with morphologically complex anaphors such as caki-casin and ku-casin, for which the models selected long-distance antecedents in 66.7% of cases for GPT-3.5-turbo, 72.5% for GPT-4, and 50% for GPT-4o. These results suggest that the models do not replicate the nuanced patterns of native speaker judgments, particularly in contexts involving morphological or syntactic complexity. However, despite these discrepancies, the models—especially GPT-4o—did exhibit some sensitivity to semantic constraints. In gender-controlled conditions, GPT-4o selected the appropriate local antecedent for ku-casin in 95% of cases in Experiment 1 and 70% in Experiment 2, and the correct long-distance antecedent for kunye in 90% of both experiments. This indicates that while LLMs do not fully internalize binding principles in a native-like way, they are capable of utilizing lexical-semantic cues such as gender to guide antecedent resolution. The findings highlight both the potential and limitations of current LLMs at the syntax-semantics interface and underscore the importance of evaluating these models on linguistically rich and typologically diverse phenomena to gain a deeper understanding of their representational capabilities and theoretical adequacy. [Collapse]
  Keywords: anaphor, antecedent, binding, large language model, syntax-semantics interface
• Korean Fuzzy Number Words: A Window onto Number Representations and Number-word Pragmatics
  by Choon-Kyu Lee & Rochel Gelman
  J. CS. 2025, 26(2), 217-226;
  Abstract Twenty-three adult native speakers of Korean participated in an appropriateness judgment task involving pre-recorded utterances of exact and fuzzy number words. Our results indicate that the use or interpretation of a fuzzy number word is judged to be appropriate whenever the corresponding point val... [Read more]
  Abstract Twenty-three adult native speakers of Korean participated in an appropriateness judgment task involving pre-recorded utterances of exact and fuzzy number words. Our results indicate that the use or interpretation of a fuzzy number word is judged to be appropriate whenever the corresponding point value is anywhere inside the range bounded by the natural numbers constituting the fuzzy number word. Results also suggest that the use of a fuzzy number word might be considered more natural as an input in the form of a request or command than as an output in the form of an estimate. [Collapse]
  Keywords: fuzzy number words, semantics-pragmatics interface, exact number system, approximate number system
• Large Language Models and Human Cognition: An Optimistic Perspective
  by Antoine Blais
  J. CS. 2025, 26(1), 1-44;
  Abstract Large Language Models (LLMs) are deep learning-based text generation tools that have shown remarkable improvement in producing coherent discourse and displaying unexpected abilities. This article explores how LLMs can contribute to our understanding of human language and cognition. The author argues... [Read more]
  Abstract Large Language Models (LLMs) are deep learning-based text generation tools that have shown remarkable improvement in producing coherent discourse and displaying unexpected abilities. This article explores how LLMs can contribute to our understanding of human language and cognition. The author argues that viewing LLMs merely as word predictors that mimic human language behavior oversimplifies their underlying mechanisms and representational capabilities. LLMs function as information acquisition and processing systems and, from a connectionist perspective, can serve as useful models of human cognition – or at least of certain aspects of it. The article begins by providing a brief account of criticisms concerning LLMs’ limitations, followed by an examination of the nature of representations within these models and a discussion on their architectural components. It further presents LLMs as general-purpose systems, highlighting their emerging non-linguistic capabilities. It is suggested that LLMs may have the potential to capture and effectively apply cultural constructs, which are primarily conveyed through language and encapsulate useful 'programs' for addressing a variety of tasks. Additionally, the article briefly examines the possibility of top-down processing and consciousness in these models. Ultimately, the author proposes that current and future generations of LLMs can contribute to a deeper understanding of human language activity and cognition, encouraging cognitive scientists to view them as more than mere engineering tools designed to mimic human language. [Collapse]
  Keywords: Large language model, deep learning, language and cognition, model of cognition, general-purpose system
• The Effect of Numerical Syntax on Number Comparison in Children
  by Joonkoo Park, Diego Guerrero, Jihyun Hwang and Rachael McCollum
  J. CS. 2025, 26(1), 45-79;
  Abstract While much is documented and theorized about how children acquire the meaning of small numbers expressed in simplex numerals (number words that cannot be decomposed further), relatively little is known about how children come to understand complex numerals (that are composed of simplex numerals). We... [Read more]
  Abstract While much is documented and theorized about how children acquire the meaning of small numbers expressed in simplex numerals (number words that cannot be decomposed further), relatively little is known about how children come to understand complex numerals (that are composed of simplex numerals). We aimed to investigate how children make sense of complex numerals by assessing how they compare large numbers. In a novel task, children compared the numerical values of two large numbers that differed only in one syntactic position (e.g., four hundred twenty chairs vs. six hundred twenty chairs). Together in two studies, with Korean- and English-speaking children, we demonstrate that children including those with limited counting fluency (e.g., not counting past 49 or 99) are able to compare large numbers in the hundreds and the hundred-thousands and that this ability correlates with their counting fluency. At the same time, children find it more difficult to compare two complex-numeral phrases (as the example above) than two simplex-numeral phrases with the same number of words (e.g., four little yellow chairs vs. six little yellow chairs). These results suggest that syntactic complexity of complex numerals influences children’s numerical thinking, which is consistent with the idea that children’s implicit understanding of numerical syntax contributes to building generative number concepts. [Collapse]
  Keywords: Number acquisition, numerical syntax, number comparison
• Models of Metaphor Identification: Observations and Insights
  by Ahmed Alharbi
  J. CS. 2025, 26(1), 81-109;
  Abstract This paper will consider a number of recently offered procedures and models of metaphor identification in the literature. The purpose is to evaluate their possible significance for application to the detection of conceptual metaphors in corpora. It is on the basis of such an evaluation that a new co... [Read more]
  Abstract This paper will consider a number of recently offered procedures and models of metaphor identification in the literature. The purpose is to evaluate their possible significance for application to the detection of conceptual metaphors in corpora. It is on the basis of such an evaluation that a new corpus-based model of metaphor identification is proposed. Compared to most previous ones, this model goes beyond the mere act of tracking the surface linguistic forms of metaphors in discourse to identifying the underlying conceptual metaphors that give rise to them. In so doing, a combination of automatic and manual means is employed. The two together have proved to be efficient in accelerating the process of revealing the conceptual bases underpinning patterns of linguistic metaphors in a particular corpus of texts. The proposed model holds important empirical implications as it highlights how conceptual metaphors operate and can be identified in a discourse context. It can therefore be utilized in the development of a simplified and generalizable framework capable of facilitating the researcher’s ability to detect and analyze metaphorical language. [Collapse]
  Keywords: conceptual metaphor, corpus, metaphor identification, semi-automatic model